DescTools

https://www.rdocumentation.org/packages/DescTools/versions/0.99.29
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### Excel Instance Example

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/GetNewXL

A Windows-specific example demonstrating how to obtain a handle to a new Excel instance.

```R
# NOT RUN {
 # Windows-specific example
# get a handle to a new excel instance
xl <- GetNewXL()
# }
```

--------------------------------

### BootCI Examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/BootCI

Examples demonstrating univariate and bivariate bootstrap confidence interval calculations.

```R
# NOT RUN {
set.seed(1984)
BootCI(d.pizza$temperature, FUN=mean, na.rm=TRUE, bci.method="basic")
BootCI(d.pizza$temperature, FUN=mean, trim=0.1, na.rm=TRUE, bci.method="basic")

BootCI(d.pizza$temperature, FUN=Skew, na.rm=TRUE, bci.method="basic")

BootCI(d.pizza$operator, d.pizza$area, FUN=CramerV)

spearman <- function(x,y) cor(x, y, method="spearman", use="p")
BootCI(d.pizza$temperature, d.pizza$delivery_min, FUN=spearman)
# }
```

--------------------------------

### Eps Example Placeholder

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/Eps

Placeholder example block provided in the package documentation.

```R
# NOT RUN {
## find!

# }
```

--------------------------------

### Initialize and Manage PowerPoint Presentations in R

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/PowerPoint%20Interface

Functions to start a new PowerPoint instance, get the current instance, and add new slides to a presentation. `GetNewPP` creates a new instance and presentation, while `GetCurrPP` retrieves an existing one. `PpAddSlide` inserts a new slide at a specified position.

```R
GetNewPP(visible = TRUE, template = "Normal")
GetCurrPP()
PpAddSlide(pos = NULL, pp = DescToolsOptions("lastPP"))
```

--------------------------------

### Install RDCOMClient from Binary URL

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/DescTools-package

Alternative installation method using a direct binary URL for specific R versions on Windows.

```R
url <- "http://www.omegahat.net/R/bin/windows/contrib/3.5.1/RDCOMClient_0.93-0.zip"
install.packages(url, repos=NULL, type="binary")
```

--------------------------------

### Execute BinTree and PlotBinTree examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/BinTree

Examples demonstrating tree generation and visualization, including a complex Titanic dataset plot.

```R
# NOT RUN {
BinTree(12)

x <- sort(sample(100, 24))
z <- PlotBinTree(x, cex=0.8)


# Plot example - Titanic data, for once from a somwhat different perspective
tab <- apply(Titanic, c(2,3,4), sum)
cprob <- c(1, prop.table(apply(tab, 1, sum))
           , as.vector(aperm(prop.table(apply(tab, c(1,2), sum), 1), c(2, 1)))
           , as.vector(aperm(prop.table(tab, c(1,2)), c(3,2,1)))
)

PlotBinTree(round(cprob[BinTree(length(cprob))],2), horiz=TRUE, cex=0.8,
            main="Titanic")
text(c("sex","age","survived"), y=0, x=c(1,2,3)+1)
# }
```

--------------------------------

### Trim function examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/Trim

Examples demonstrating trimming by fraction and by fixed count, including verification of the trimmed indices.

```R
# NOT RUN {
## generate data
set.seed(1234)     # for reproducibility
x <- rnorm(10)     # standard normal
x[1] <- x[1] * 10  # introduce outlier

## Trim data
x
Trim(x, trim=0.1)

## Trim fixed number, say cut the 3 extreme elements from each end
Trim(x, trim=3)

## check function
s <- sample(10:20)
s.tr <- Trim(s, trim = 2)
setequal(c(s[attr(s.tr, "trim")], s.tr), s)
# }
```

--------------------------------

### Install RDCOMClient from Omegahat

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/DescTools-package

Standard installation command for the RDCOMClient package required for MS-Office features.

```R
install.packages("RDCOMClient", repos="http://www.omegahat.net/R")
```

--------------------------------

### Execute Date Manipulation Examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/Date%20Functions

Examples demonstrating extraction of date components, setting day values, and calculating month-end dates.

```R
# NOT RUN {
x <- Today()    # the same as Sys.Date() but maybe easier to remember..

Year(x)
Quarter(x)

Month(x)
Month(x, fmt = "mm", lang="engl")
Month(x, fmt = "mm", lang="local")
Month(x, fmt = "mmm", lang="engl")
Month(x, fmt = "mmm", lang="local")

Week(x)

Day(x)
Day(x) <- 20
x

Weekday(x)
Weekday(x, fmt = "dd", lang="engl")
Weekday(x, fmt = "dd", lang="local")
Weekday(x, fmt = "ddd", lang="engl")
Weekday(x, fmt = "ddd", lang="local")

YearDay(x)

IsWeekend(x)

IsLeapYear(x)

# let's generate a time sequence by weeks
Month(seq(from=as.Date(Sys.Date()), to=Sys.Date()+150, by="weeks"), fmt="mm")

LastDayOfMonth(as.Date(c("2014-10-12","2013-01-31","2011-12-05")))

# }
```

--------------------------------

### BarText Examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/BarText

Examples demonstrating how to use BarText with simple vectors and complex matrices, including both vertical and horizontal orientations.

```R
# NOT RUN {
# simple vector
x <- c(453, 44, 56, 34)
b <- barplot(x)
BarText(x, b, x)

# more complicated
b <- barplot(VADeaths, horiz = FALSE, col=hblue, beside = TRUE)
BarText(VADeaths, b=b, horiz = FALSE, beside = TRUE, cex=0.8)
BarText(VADeaths, b=b, horiz = FALSE, beside = TRUE, cex=0.8, top=FALSE,
        col="white", font=2)

b <- barplot(VADeaths, horiz = TRUE, col=hblue, beside = TRUE)
BarText(VADeaths, b=b, horiz = TRUE, beside = TRUE, cex=0.8)

b <- barplot(VADeaths)
BarText(VADeaths, b=b)

b <- barplot(VADeaths, horiz = TRUE)
BarText(VADeaths, b=b, horiz = TRUE, col="red", cex=1.5)
# }
```

--------------------------------

### DivCoefMax Usage Examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/DivCoefMax

Examples demonstrating the calculation of maximal spatial diversity and maximization with ultrametric dissimilarities.

```R
# NOT RUN {
par.safe <- par()$mar
data(elec88)
par(mar = c(0.1, 0.1, 0.1, 0.1))
# Departments of France.
area.plot(elec88$area)

# Dissimilarity matrix.
d0 <- dist(elec88$xy)

# Frequency distribution maximizing spatial diversity in France
# according to Rao's quadratic entropy.
France.m <- DivCoefMax(d0)
w0 <- France.m$vectors$num
v0 <- France.m$value
(1:94) [w0 > 0]

# Smallest circle including all the 94 departments.
# The squared radius of that circle is the maximal value of the
# spatial diversity.
w1 = elec88$xy[c(6, 28, 66), ]
w.c = apply(w1 * w0[c(6, 28, 66)], 2, sum)
symbols(w.c[1], w.c[2], circles = sqrt(v0), inc = FALSE, add = TRUE)
s.value(elec88$xy, w0, add.plot = TRUE)
par(mar = par.safe)


# Maximisation of Rao's diversity coefficient
# with ultrametric dissimilarities.
data(microsatt)
mic.genet <- count2genet(microsatt$tab)
mic.dist <- dist.genet(mic.genet, 1)
mic.phylog <- hclust2phylog(hclust(mic.dist))
plot.phylog(mic.phylog)
mic.maxpond <- DivCoefMax(mic.phylog$Wdist)$vectors$num
dotchart.phylog(mic.phylog, mic.maxpond)
# }
```

--------------------------------

### CollapseTable Examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/CollapseTable

Examples demonstrating how to collapse table dimensions and re-label levels using the CollapseTable function.

```R
# NOT RUN {
# create some sample data in table form
sex <- c("Male", "Female")
age <- letters[1:6]
education <- c("low", 'med', 'high')
data <- expand.grid(sex=sex, age=age, education=education)
counts <- rpois(36, 100)
data <- cbind(data, counts)
t1 <- xtabs(counts ~ sex + age + education, data=data)

Desc(t1)

##                  age   a   b   c   d   e   f
## sex    education
## Male   low           119 101 109  85  99  93
##        med            94  98 103 108  84  84
##        high           81  88  96 110 100  92
## Female low           107 104  95  86 103  96
##        med           104  98  94  95 110 106
##        high           93  85  90 109  99  86


# collapse age to 3 levels
t2 <- CollapseTable(t1, age=c("A", "A", "B", "B", "C", "C"))
Desc(t2)

##                  age   A   B   C
## sex    education
## Male   low           220 194 192
##        med           192 211 168
##        high          169 206 192
## Female low           211 181 199
##        med           202 189 216
##        high          178 199 185


# collapse age to 3 levels and pool education: "low" and "med" to "low"
t3 <- CollapseTable(t1, age=c("A", "A", "B", "B", "C", "C"),
    education=c("low", "low", "high"))
Desc(t3)

##                  age   A   B   C
## sex    education
## Male   low           412 405 360
##        high          169 206 192
## Female low           413 370 415
##        high          178 199 185



# change labels for levels of education to 1:3
t4 <- CollapseTable(t1,  education=1:3)
Desc(t4)

##                  age   a   b   c   d   e   f
## sex    education
## Male   1             119 101 109  85  99  93
##        2              94  98 103 108  84  84
##        3              81  88  96 110 100  92
## Female 1             107 104  95  86 103  96
##        2             104  98  94  95 110 106
##        3              93  85  90 109  99  86
# }
```

--------------------------------

### Example of Matrix Power Calculation

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/matpow

Demonstrates the usage of the `%^%` operator for calculating matrix powers and verifies the results against direct matrix multiplication. The example is not run by default.

```R
# NOT RUN {
A <- cbind(1, 2 * diag(3)[,-1])
A
A %^% 2
stopifnot(identical(A, A %^% 1),
          A %^% 2 == A %*% A)
# }
```

--------------------------------

### Examples of Order Statistic Calculations

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/Order

Examples demonstrating the use of dOrder, pOrder, and rOrder with various distributions and parameters.

```R
# NOT RUN {
dOrder(2:4, dnorm, pnorm, mean = 0.5, sd = 1.2, mlen = 5, j = 2)
dOrder(2:4, distn = "norm", mean = 0.5, sd = 1.2, mlen = 5, j = 2)
dOrder(2:4, distn = "exp", mlen = 2, j = 2)
pOrder(2:4, distn = "exp", rate = 1.2, mlen = 2, j = 2)
rOrder(5, qgamma, shape = 1, mlen = 10, j = 2)
# }
```

--------------------------------

### PlotDot Examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/PlotDot

Various examples demonstrating basic plotting, error bars, grouped data, and custom formatting.

```R
# NOT RUN {
PlotDot(VADeaths, main = "Death Rates in Virginia - 1940")
op <- par(xaxs = "i")  # 0 -- 100%
PlotDot(t(VADeaths), xlim = c(0,100),
        main = "Death Rates in Virginia - 1940")
par(op)

# add some error bars
PlotDot(VADeaths, main="Death Rates in Virginia - 1940", col="red", pch=21,
        args.errbars = list(from=VADeaths-2, to=VADeaths+2, mid=VADeaths,
                            cex=1.4))

# add some other values
PlotDot(VADeaths+3, pch=15, col="blue", add=TRUE, labels=NA)

# same as PlotDotCI
xci <- do.call(rbind, tapply( d.pizza$delivery_min, d.pizza$driver,
                              MeanCI, conf.level=0.99, na.rm=TRUE))

PlotDot(xci[,1], main="delivery_min ~ driver", pch=21, bg="grey80", col="black",
        args.errbars = list(from=xci[,2], to=xci[,3], mid=xci[,1], lwd=2, col="grey40", cex=1.5),
        xlim=c(15,35), panel.before=grid())

# with group data
x <- with(d.pizza, tapply(temperature, list(area, driver), mean, na.rm=TRUE))

PlotDot(x, gdata = tapply(d.pizza$temperature, d.pizza$driver, mean, na.rm=TRUE),
        gpch = 15)

# special format
par(lend=1)

PlotDot(VADeaths, main="Death Rates in Virginia - 1940", pch="|", lcolor = hecru, col=hred,
        args.errbars = list(from=VADeaths-2, to=VADeaths+2, mid=VADeaths,
                            cex=1.3, lwd=8, code=0, col=hgreen))

# Error bars for binomial confidence intervals
tab <- table(d.pizza$driver, d.pizza$wine_delivered)
xci <- SetNames(BinomCI(tab[,1], rowSums(tab)), rownames=rownames(tab))
PlotDot(xci[,1], main="wine delivered ~ driver ", xlim=c(0,1),
        args.errbars=list(from=xci[,-1], mid=xci[,1], pch=21))
```

--------------------------------

### WrdCellRange Example

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/WrdCellRange

Demonstrates selecting a range of cells in a Word table. This example is Windows-specific and requires an active Word application instance.

```R
# NOT RUN {
# Windows-specific example
wrd <- GetNewWrd()
WrdTable(nrow=3, ncol=3, wrd=wrd)
crng <- WrdCellRange(rstart=c(1,2), rend=c(2,3))
crng$Select()
# }
```

--------------------------------

### Example: Rotating a Triangle with DescTools

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/Rotate

Demonstrates rotating a triangle using the Rotate function. The example visualizes multiple rotations of a triangle around the origin.

```r
# NOT RUN {
# let's have a triangle
Canvas(main="Rotation")
x <- DrawRegPolygon(nv=3)[[1]]

# and rotate
sapply( (0:3) * pi/6, function(theta) {
  xy <- Rotate( x=x, theta=theta )
  polygon(xy, col=SetAlpha("blue", 0.2))
} )

abline(v=0, h=0)
# }
```

--------------------------------

### Examples of Untable usage

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/Untable

Various examples demonstrating how to expand tables, data frames, and weight vectors into original data.

```R
# NOT RUN {
d.titanic <- Untable(Titanic)
str(d.titanic)

# ... not the same as:
data.frame(Titanic)


tab <- table(set1=sample(letters[1:5], size=40, replace=TRUE), 
             set2=sample(letters[11:15], size=40, replace=TRUE))
Untable(tab)


# return a numeric vector by setting type and coerce to a vector by [,]
Untable(c(6,2,2), type="as.numeric")[,]


# how to produce the original list based on frequencies, given as a data.frame
d.freq <- data.frame(xtabs(Freq ~ Sex + Survived, data=Titanic))

# a data list with each individual
d.data <- Untable( xtabs(c(1364, 126, 367, 344) ~ ., 
             expand.grid(levels(d.freq$Sex),levels(d.freq$Survived)))) 
head(d.data)

# expand a weights vector
Untable(c(1,4,5), dimnames=list(c("Zurich","Berlin","London")))

# and the same with a numeric vector 
Untable(c(1,4,5), dimnames=list(c(5,10,15)), type="as.numeric")[,]
# ... which again is nothing else than
rep(times=c(1,4,5), x=c(5,10,15))

# the data.frame interface
d.freq <- data.frame(f1=c("A","A","B","B"), f2=c("C","D","C","D"), Freq=c(1,2,3,4))
Untable(d.freq)
# }
```

--------------------------------

### ExtrVal Usage Examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/ExtrVal

Demonstrates how to use the dExtrVal, pExtrVal, qExtrVal, and rExtrVal functions with different distributions and parameters. The examples show usage with both explicit density/distribution/quantile functions and by specifying the distribution name.

```R
# NOT RUN {
dExtrVal(2:4, dnorm, pnorm, mean = 0.5, sd = 1.2, mlen = 5)
dExtrVal(2:4, distn = "norm", mean = 0.5, sd = 1.2, mlen = 5)
dExtrVal(2:4, distn = "exp", mlen = 2, largest = FALSE)
pExtrVal(2:4, distn = "exp", rate = 1.2, mlen = 2)
qExtrVal(seq(0.9, 0.6, -0.1), distn = "exp", rate = 1.2, mlen = 2)
rExtrVal(5, qgamma, shape = 1, mlen = 10)
p <- (1:9)/10
pexp(qExtrVal(p, distn = "exp", rate = 1.2, mlen = 1), rate = 1.2)
## [1] 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
# }
```

--------------------------------

### Example: Count Complete Cases

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/CountCompCases

Demonstrates the usage of the CountCompCases function with a sample data frame. This example is not run by default.

```R
# NOT RUN {
CountCompCases(d.pizza)
# }
```

--------------------------------

### VonNeumannTest Example Usage

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/VonNeumannTest

Demonstrates how to use the VonNeumannTest function with a sample numeric vector. This example is marked as NOT RUN, suggesting it requires specific data or environment setup.

```R
# NOT RUN {
VonNeumannTest(d.pizza$temperature)
# }
```

--------------------------------

### WrdStyle Example

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/WrdStyle

Demonstrates initializing a Word instance and retrieving the current style.

```R
# NOT RUN {
 # Windows-specific example

wrd <- GetNewWrd()
# the current stlye
WrdStyle(wrd)
# }
```

--------------------------------

### Stratified Sampling Example (systematic)

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/Strata

Demonstrates stratified sampling without replacement using the 'systematic' method with inclusion probabilities derived from the 'income' variable. Requires the same data setup as the 'srswor' example.

```r
# The same data as in Example 1
# the method is 'systematic' (unequal probability, without replacement)
# the selection probabilities are computed using the variable 'income'
s <- Strata(m,c("region", "state"), size=c(10, 5, 10, 4, 6),
            method="systematic", pik=m$income)

# extracts the observed data
data.frame(income=m[s$id, "income"], s)

# see the result using a contigency table
table(s$region, s$state)
```

--------------------------------

### Get Aspect Ratio of Current Plot (R)

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/Asp

Use Asp() to get the aspect ratio of the current plot in user coordinates. No specific setup or imports are required beyond having an active plot.

```r
Asp()
```

--------------------------------

### Manage Word Bookmarks Example

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/WrdInsertBookmark

Demonstrates creating a new Word instance, inserting a bookmark, and updating its content.

```R
# NOT RUN {
 # Windows-specific example
wrd <- GetNewWrd()
WrdText("a)\n\n\nb)", fontname=WrdGetFont()$name, fontsize=WrdGetFont()$size)
WrdInsertBookmark("chap_b")
WrdText("\n\n\nc)\n\n\n", fontname=WrdGetFont()$name, fontsize=WrdGetFont()$size)

WrdGoto("chap_b")
WrdUpdateBookmark("chap_b", "Goto chapter B and set text")
# }
```

--------------------------------

### Stratified Sampling Example (srswor)

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/Strata

Demonstrates stratified sampling without replacement using the 'srswor' method. Requires setup of artificial data and specifies sample sizes per stratum.

```r
# Example from An and Watts (New SAS procedures for Analysis of Sample Survey Data)
# generates artificial data (a 235X3 matrix with 3 columns: state, region, income).
# the variable "state" has 2 categories ('nc' and 'sc').
# the variable "region" has 3 categories (1, 2 and 3).
# the sampling frame is stratified by region within state.
# the income variable is randomly generated

m <- rbind(matrix(rep("nc",165), 165, 1, byrow=TRUE),
           matrix(rep("sc", 70), 70, 1, byrow=TRUE))
m <- cbind.data.frame(m, c(rep(1, 100), rep(2,50), rep(3,15),
                      rep(1, 30), rep(2, 40)), 1000 * runif(235))
names(m) <- c("state", "region", "income")

# computes the population stratum sizes
table(m$region, m$state)

# not run
#     nc  sc
#  1 100  30
#  2  50  40
#  3  15   0
# there are 5 cells with non-zero values
# one draws 5 samples (1 sample in each stratum)
# the sample stratum sizes are 10,5,10,4,6, respectively
# the method is 'srswor' (equal probability, without replacement)

s <- Strata(m, c("region", "state"), size=c(10, 5, 10, 4, 6), method="srswor")

# extracts the observed data
data.frame(income=m[s$id, "income"], s)

# see the result using a contigency table
table(s$region, s$state)
```

--------------------------------

### CochranQTest Example Implementation

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/CochranQTest

Demonstrates data preparation using Untable and reshape, followed by the execution of CochranQTest on a long-format dataset.

```R
# NOT RUN {
# example in: 
# http://support.sas.com/documentation/cdl/en/statugfreq/63124/PDF/default/statugfreq.pdf
# pp. S. 1824

# use expand.grid, xtabs and Untable to create the dataset
d.frm <- Untable(xtabs(c(6,2,2,6,16,4,4,6) ~ ., 
    expand.grid(rep(list(c("F","U")), times=3))), 
    colnames = LETTERS[1:3])

# rearrange to long shape    
d.long <- reshape(d.frm, varying=1:3, times=names(d.frm)[c(1:3)], 
                  v.names="resp", direction="long")


# after having done the hard work of data organisation, performing the test is a piece of cake....
CochranQTest(resp ~ time | id, data=d.long)
# }
```

--------------------------------

### GTest Example: Goodness-of-Fit Test with Raw Data

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/GTest

Shows how to perform a goodness-of-fit test using GTest when starting with raw data. It requires converting the raw data into a frequency table first.

```R
## Case B. Raw data
x <- trunc(5 * runif(100))
GTest(table(x))                # NOT 'GTest(x)'!

```

--------------------------------

### Winsorize Data Examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/Winsorize

Demonstrates basic Winsorization and custom boundary setting using Small and Large functions.

```R
# NOT RUN {
## generate data
set.seed(1234)     # for reproducibility
x <- rnorm(10)     # standard normal
x[1] <- x[1] * 10  # introduce outlier

## Winsorize data
x
Winsorize(x)

# use Large and Small, if a fix number of values should be winsorized (here k=3):
Winsorize(x, minval=tail(Small(x, k=3), 1), maxval=head(Large(x, k=3), 1))
# }
```

--------------------------------

### Abstract Example

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/ColumnWrap

Example usage of the Abstract function with the d.pizza dataset.

```R
# NOT RUN {
Abstract(d.pizza)
# }
```

--------------------------------

### Initialize Excel Instance

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/GetNewXL

Standard usage for starting a new Excel application instance.

```R
GetNewXL(visible = TRUE, newdoc = TRUE)
```

--------------------------------

### Example of IsDichotomous

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/IsDichotomous

Basic usage example for checking if a sampled vector is dichotomous.

```R
# NOT RUN {
IsDichotomous(sample(10, 5, replace=TRUE))
# }
```

--------------------------------

### Format and Fmt Usage Examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/Format

Demonstrates various formatting techniques for dates, matrices, and numeric values, including scientific and engineering notations. Also shows how to manage custom format templates using Fmt.

```R
# NOT RUN {
Format(as.Date(c("2014-11-28", "2014-1-2")), fmt="ddd, d mmmm yyyy")
Format(as.Date(c("2014-11-28", "2014-1-2")), fmt="ddd, d mmmm yyyy", lang="engl")

x <- pi * 10^(-10:10)

Format(x, digits=3, fmt="%", sci=NA)
Format(x, digits=4, sci=c(4, 6), leading = "drop", width=9, align=".")


# format a matrix
m <- matrix(runif(100), nrow=10,
            dimnames=list(LETTERS[1:10], LETTERS[1:10]))

Format(m, digits=1)

# engineering format
Format(x, fmt="eng",  digits=2)
Format(x, fmt="engabb", leading="00", digits=2)
# combine with grams [g]
paste(Format(x, fmt="engabb", leading="00", digits=2), "g", sep="")

# example form symnum
pval <- rev(sort(c(outer(1:6, 10^-(1:3)))))
noquote(cbind(Format(pval, fmt="p"), Format(pval, fmt="*")))

# use Fmt() to get and define new formats stored as option
Fmt()                        # all defined formats
Fmt("abs")                   # only format named "abs"
Fmt("nexist")                # only format named "nexist" (nonexisting)
Fmt("abs", "per", "nexist")
Fmt("abs", digits=3)         # get Fmt("abs") and overwrite digits
Fmt("abs", na.form="-")      # get Fmt("abs") and add user defined na.form

# define totally new format and store as option
Fmt(nob=as.fmt(digits=10, na.form="nodat"))

# overwrite an existing format
Fmt(nob=Fmt("nob", digits=5))
Fmt("nob")

# change the character to be used as the decimal point
opt <- options(OutDec=",")
Format(1200, digits=2, big.mark = ".")
options(opt)
# }
```

--------------------------------

### Install DescTools Package

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29

Use this command to install the DescTools package from CRAN.

```R
install.packages('DescTools')
```

--------------------------------

### Apply Paragraph Formatting in Word

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/WrdParagraphFormat

Example demonstrating how to initialize a Word instance and apply specific paragraph alignment and indentation settings.

```R
# NOT RUN {
# Windows-specific example
wrd <- GetNewWrd()  # get the handle to a new word instance

WrdParagraphFormat(wrd=wrd) <- list(Alignment=wdConst$wdAlignParagraphLeft,
                                    LeftIndent=42.55)

ToWrd("Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy
eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua.
At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd
gubergren, no sea takimata sanctus est.\n", wrd=wrd)

# reset
WrdParagraphFormat(wrd=wrd) <- list(LeftIndent=0)
# }
```

--------------------------------

### ColorLegend Examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/ColorLegend

Various examples demonstrating how to position and style color legends on a plot.

```R
# NOT RUN {
plot(1:15,, xlim=c(0,10), type="n", xlab="", ylab="", main="Colorstrips")

# A
ColorLegend(x="right", inset=0.1, labels=c(1:10))

# B: Center the labels
ColorLegend(x=1, y=9, height=6, col=colorRampPalette(c("blue", "white", "red"),
  space = "rgb")(5), labels=1:5, cntrlbl = TRUE)

# C: Outer frame
ColorLegend(x=3, y=9, height=6, col=colorRampPalette(c("blue", "white", "red"),
  space = "rgb")(5), labels=1:4, frame="grey")

# D
ColorLegend(x=5, y=9, height=6, col=colorRampPalette(c("blue", "white", "red"),
  space = "rgb")(10), labels=sprintf("%.1f",seq(0,1,0.1)), cex=0.8)

# E: horizontal shape
ColorLegend(x=1, y=2, width=6, height=0.2, col=rainbow(500), labels=1:5,horiz=TRUE)

# F
ColorLegend(x=1, y=14, width=6, height=0.5, col=colorRampPalette(
  c("black","blue","green","yellow","red"), space = "rgb")(100), horiz=TRUE)

# G
ColorLegend(x=1, y=12, width=6, height=1, col=colorRampPalette(c("black","blue",
            "green","yellow","red"), space = "rgb")(10), horiz=TRUE, border="black")

text(x = c(8,0.5,2.5,4.5,0.5,0.5,0.5)+.2, y=c(14,9,9,9,2,14,12), LETTERS[1:7], cex=2)

# }
```

--------------------------------

### Example: Convert String to ASCII and Back

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/AscToChar

Demonstrates converting a string to its ASCII codes using CharToAsc and then converting those codes back to characters using AscToChar. Shows how to use strsplit for individual characters.

```R
# NOT RUN {
(x <- CharToAsc("Silvia"))

# will be pasted together
AscToChar(x)

# use strsplit if the single characters are needed
strsplit(AscToChar(x), split=NULL)

# this would be an alternative, but the latter would be of class raw
DecToHex(CharToAsc("Silvia"))
charToRaw("Silvia")
# }
```

--------------------------------

### Example: Generate and Time Primes

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/Primes

Demonstrates how to generate a list of primes up to 100 and measure the time taken to generate primes up to 1000. Includes an assertion to verify the count of primes.

```R
# NOT RUN {
(p1 <- Primes(100))
system.time(p1k <- Primes(1000)) # still lightning ..

stopifnot(length(p1k) == 168)

# }
```

--------------------------------

### CatTable Example Usage

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/CatTable

Demonstrates how to prepare data and invoke CatTable to handle multi-row table printing.

```R
# NOT RUN {
# used in bivariate description functions
Desc(temperature ~ cut(delivery_min, breaks=40), data=d.pizza)


txt <- c( 
   paste(sample(letters, 500, replace=TRUE), collapse="")
 , paste(sample(letters, 500, replace=TRUE), collapse="")
 , paste(sample(letters, 500, replace=TRUE), collapse="")
)
txt <- paste(c("aaa","bbb","ccc"), txt, sep="")

CatTable(txt, nrepchars=3, wcol=5)
# }
```

--------------------------------

### DivCoef Examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/DivCoef

Example usage scenarios for DivCoef using ecological and DNA methylation datasets.

```R
# NOT RUN {
# data(ecomor)
# dtaxo <- dist.taxo(ecomor$taxo)
# DivCoef(ecomor$habitat, dtaxo)

# data(humDNAm)
# DivCoef(humDNAm$samples, sqrt(humDNAm$distances))
# }
```

--------------------------------

### Manage DescTools Options

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/DescToolsOptions

Demonstrates retrieving, setting, and resetting package options.

```R
# get some potentially undefined option, while taking a user default and
# overriding system defaults
DescToolsOptions("stamp", default="Condor, 2016")

# get an undefined option, should return default
DescToolsOptions("stampede", default="Condor, 2016")

# set options, while getting the old values
opt <- DescToolsOptions(plotit=789, lang="portugues")
DescToolsOptions()
# output the old values
opt

# just a single argument
DescToolsOptions(digits=2)

# reset the old values
DescToolsOptions(opt)
DescToolsOptions()

# reset factory defaults
DescToolsOptions(reset=TRUE)
```

--------------------------------

### Zodiac Function Examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/Zodiac

Examples demonstrating zodiac calculation for specific dates and random date samples.

```R
# NOT RUN {
Zodiac(as.Date(c("1937-07-28", "1936-06-01", "1966-02-25",
                 "1964-11-17", "1972-04-25")), lang="deu")

d <- sample(seq(as.Date("2015-01-01"), as.Date("2015-12-31"), 1), 120)
z <- Zodiac(d)
Desc(z)
# }
```

--------------------------------

### TukeyBiweight Example

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/TukeyBiweight

A basic example of calculating the Tukey's biweight for a vector of random normal values.

```R
# NOT RUN {
TukeyBiweight(rnorm(100))
# }
```

--------------------------------

### Frechet Distribution Examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/Frechet

Demonstrates calculating density, distribution, quantiles, and generating random values for the Frechet distribution.

```R
# NOT RUN {
dFrechet(2:4, 1, 0.5, 0.8)
pFrechet(2:4, 1, 0.5, 0.8)
qFrechet(seq(0.9, 0.6, -0.1), 2, 0.5, 0.8)
rFrechet(6, 1, 0.5, 0.8)
p <- (1:9)/10
pFrechet(qFrechet(p, 1, 2, 0.8), 1, 2, 0.8)
## [1] 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
# }
```

--------------------------------

### Example of StrPos

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/StrPos

Example usage of StrPos to find the position of a character within a factor level vector.

```R
# NOT RUN {
StrPos(x = levels(d.pizza$driver), pattern = "t")
# }
```

--------------------------------

### Execute Excel range imports

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/XLGetRange

Examples demonstrating how to specify file paths or use the current Excel selection.

```R
# NOT RUN {
 # Windows-specific example

XLGetRange(file="C:\My Documents\data.xls",
           sheet="Sheet1",
           range=c("A2:B5","M6:X23","C4:D40"))


# if the current region has to be read (incl. a header), place the cursor in the interesting region
# and run:
d.set <- XLGetRange(header=TRUE)
```

--------------------------------

### HuberM Examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/HuberM

Examples demonstrating basic usage, handling of zero scale, and bootstrap confidence intervals.

```R
# NOT RUN {
HuberM(c(1:9, 1000))
mad   (c(1:9, 1000))

set.seed(7)
x <- c(round(rnorm(1000), 1), round(rnorm(50, m=10, sd = 10)))
HuberM(x, conf.level=0.95)


# }
# NOT RUN {
# scale zero
HuberM(rep(9, 100))
mad   (rep(9, 100))

# bootstrap confidence intervals
HuberM(x, conf.level=0.95, ci.type="boot")
# }
```

--------------------------------

### GenExtrVal Distribution Examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/GenExtrVal

Example usage of GenExtrVal functions for density, probability, quantile, and random generation.

```R
# NOT RUN {
dGenExtrVal(2:4, 1, 0.5, 0.8)
pGenExtrVal(2:4, 1, 0.5, 0.8)
qGenExtrVal(seq(0.9, 0.6, -0.1), 2, 0.5, 0.8)
rGenExtrVal(6, 1, 0.5, 0.8)
p <- (1:9)/10
pGenExtrVal(qGenExtrVal(p, 1, 2, 0.8), 1, 2, 0.8)
## [1] 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
# }
```

--------------------------------

### ErrBars Usage Examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/ErrBars

Examples demonstrating how to add vertical and horizontal error bars to barplots and dotcharts.

```R
# NOT RUN {
par(mfrow=c(2,2))
b <- barplot(1:5, ylim=c(0,6))
ErrBars(from=1:5-rep(0.5,5), to=1:5+rep(0.5,5), pos=b, length=0.2)

# just on one side
b <- barplot(1:5, ylim=c(0,6))
ErrBars(from=1:5, to=1:5+rep(0.5,5), pos=b, length=0.2, col="red", code=2, lwd=2)

b <- barplot(1:5, xlim=c(0,6), horiz=TRUE)
ErrBars(from=1:5, to=1:5+rep(0.2,5), pos=b, horiz=TRUE,  length=0.2, col="red", code=2, lwd=2)

par(xpd=FALSE)
dotchart(1:5, xlim=c(0,6))
ErrBars(from=1:5-rep(0.2,5), to=1:5+rep(0.2,5), horiz=TRUE, length=0.1)
# }
```

--------------------------------

### StrTrunc Examples

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/StrTrunc

Demonstrates string truncation and optional right justification using formatC.

```R
# NOT RUN {
set.seed(1789)
x <- sapply(seq(10),  function(x) paste(sample(letters, sample(20,1)),collapse=""))
x

StrTrunc(x, maxlen=10)

# right justification
formatC(StrTrunc(x, maxlen=10), width = 10, flag=" ")
# }
```

--------------------------------

### Insert a Table in Word

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/WrdTable

Demonstrates initializing a new Word instance and inserting a 3x3 table. This example is Windows-specific.

```R
# NOT RUN {
 # Windows-specific example
wrd <- GetNewWrd()
WrdTable(nrow=3, ncol=3, wrd=wrd)
# }
```

--------------------------------

### Mathematical Examples for UnirootAll

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/UnirootAll

Demonstrates finding roots for well-behaved and difficult mathematical functions using UnirootAll. Requires the 'curve' and 'points' functions for visualization.

```R
# a well-behaved case...
fun <- function (x) cos(2*x)^3

curve(fun(x), 0, 10,main = "UnirootAll")

All <- UnirootAll(fun, c(0, 10))
points(All, y = rep(0, length(All)), pch = 16, cex = 2)

# a difficult case...
f <- function (x) 1/cos(1+x^2)
AA <- UnirootAll(f, c(-5, 5))
curve(f(x), -5, 5, n = 500, main = "UnirootAll")
points(AA, rep(0, length(AA)), col = "red", pch = 16)

f(AA)  # !!!
```

--------------------------------

### SampleTwins Example Usage

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/SampleTwins

Example demonstrating how to prepare data and draw a twin sample using the SampleTwins function.

```R
# NOT RUN {
m <- rbind(matrix(rep("nc",165), 165, 1, byrow=TRUE), 
           matrix(rep("sc", 70), 70, 1, byrow=TRUE))
m <- cbind.data.frame(m, c(rep(1, 100), rep(2,50), rep(3,15), 
                           rep(1,30), rep(2,40)), 1000*runif(235))
names(m) <- c("state","region","income")

# this would be our sample to be reproduced by a twin sample
d.smp <- m[sample(nrow(m), size=10, replace=TRUE),]

# draw the sample
s <- SampleTwins(x = m, stratanames=c("state","region"), twins = d.smp, method="srswor")

d.twin <- m[s$id,]
d.twin
# }
```

--------------------------------

### Basic PlotFaces Example

Source: https://www.rdocumentation.org/packages/DescTools/versions/0.99.29/topics/PlotFaces

Demonstrates a simple use case of PlotFaces with a small data matrix.

```R
# NOT RUN {
PlotFaces(rbind(1:3,5:3,3:5,5:7))
```
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