seMean: se functions

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

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

Usage

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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

See Also

asymp.test that used estimated standard error for asymptotic parametric tests.

Examples

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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)


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