# seMean: se functions In asympTest: A Simple R Package for Classical Parametric Statistical Tests and Confidence Intervals in Large Samples

## Description

se functions compute the Standard Error of respectively mean, variance, difference of means, of variances and ratio of means and variances.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21``` ```seMean(x,...) ## Default S3 method: seMean(x,...) seVar(x,...) ## Default S3 method: seVar(x,...) seDMean(x,...) ## Default S3 method: seDMean(x, y, rho = 1, ...) seDMeanG(x,...) ## Default S3 method: seDMeanG(x, y,...) seDVar(x,...) ## Default S3 method: seDVar(x, y, rho = 1, ...) seRMean(x,...) ## Default S3 method: seRMean(x, y, r0,...) seRVar(x,...) ## Default S3 method: seRVar(x, y, r0,...) ```

## Arguments

 `x` a (non-empty) numeric vector of data values. `y` an optional (non-empty) numeric vector of data values. `rho` optional parameter for penalization (or enhancement) of the contribution of the second parameter. `r0` an optional parameter for ratio of means (seRMean) or variances (seRVar). It acts as parameter r in seDMean and seDVar. Defaults are mean(x)/mean(y) in seRMean and var(x)/var(y) for seRVar. `...` further arguments to be passed to or from methods.

## Details

se functions performs classical standard error estimation for parameters mean, variance, difference of means or variances, ratio of means or variances.

## Value

Return the value of the estimated standard error for the corresponding parameter.

## Author(s)

J.-F. Coeurjolly, R. Drouilhet, P. Lafaye de Micheaux, J.-F. Robineau

## References

Coeurjolly, J.F. Drouilhet, R. Lafaye de Micheaux, P. Robineau, J.F. (2008) asympTest: a simple R package for performing classical parametric statistical tests and confidence intervals in large samples, The R Journal

`asymp.test` that used estimated standard error for asymptotic parametric tests.
 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```x <- rnorm(70, mean = 1, sd = 2) y <- rnorm(50, mean = 2, sd = 1) ## mean statistic asymp.test(x)\$stat mean(x)/seMean(x) ## variance statistic asymp.test(x,param="var",alt="l",param0=2)\$stat (var(x)-2)/seVar(x) ## difference of means statistic asymp.test(x,y)\$stat (mean(x)-mean(y))/seDMean(x,y) ```