simba (version 0.3-4)

diffmean: Calculate the difference in Mean between two vectors

Description

The function can be used to calculate the difference in mean between two vectors. Statistical inference is obtained through permutation. F-ratio is also calculated. For data which is not normally distributed or lacks independence. The plotting method plots the actual values of the difference in mean and F against an histogram of the results of the permuted runs.

Usage

diffmean(x, y, permutations = 1000, ...)
## S3 method for class 'dmn':
plot(x, y, which=3, two=2, ...)

Arguments

x

Numeric vector. For the plotting method the dmn-object which should be printed (results from a diffmean operation). Plotting object in the plotting method.

y

Numeric vector. Plotting object in the plotting method, optional when x has appropriate structure

permutations

Number of permutations.

which

which histogram should be plotted? 1 triggers the histogram for difference in mean, 2 the one for F. It defaults to 3: both histograms are plotted. If it is changed from default, the next argument (two) is automatically set to 1!

two

Should the histograms be printed on a divided display? And how? Can only be set if which is set to 3. Defaults to 2, which means that the display is divided in two halfs and the histogram-plots are plotted side by side. 3 causes histograms to

...

Further arguments to the plotting method or to function mean.

Value

• Returns a list giving the function call, the difference in Mean, the mean of vector x and y, the mean of means, the F-value, the significance of the difference in Mean and the significance of F, as well as the number of permutations. The results of the permutation runs can be retrieved with result$bootsM (for the difference in mean) and result$bootF (for the F-values). There is a plot method for easily illustrating the test. The difference is plotted against an histogram displaying the distribution of the permuted values.

encoding

UTF-8

Details

The two vectors do not need to share the same length but they should not be too different. Otherwise the function might give spurious results.

See Also

diffslope, diffmich

Examples

data(abis)

## create subsetting vector describing the belonging to different
## vegetationtypes
tcs.sub <- rep(0, 61)
tcs.sub[abis.env[,29]==1] <- 1
tcs.sub[abis.env[,30]==1] <- 2
tcs.sub[abis.env[,31]==1] <- 3

## check distribution
summary(as.factor(tcs.sub))

## compare vegetation types "shrubby vegetation" (shrub=2) and
## "protected by snowcover" (protect=3) regarding difference in 
## similarities
abis2.soer <- sim(abis.spec[tcs.sub==2,])
abis3.soer <- sim(abis.spec[tcs.sub==3,])
abis.23cmp <- diffmean(abis2.soer, abis3.soer)