svrVar

matrix whose rows are replicates (or a vector of replicates)

thetas

scale

Scaling factor for each squared deviation 

rscales

How to handle replicates where the statistic could
    not be estimated

na.action

if <code>TRUE</code>, center at the point estimated, if
    <code>FALSE</code> center at the mean of the replicates

The point estimate, required only if <code>mse==TRUE</code>

coef


Compute an appropriately scaled empirical variance estimate from
replicates.  The <code>mse</code> argument specifies whether the sums of
squares should be centered at the point estimate (<code>mse=TRUE</code>) or
the mean of the replicates. It is usually taken from the <code>mse</code>
component of the design object.


survey

Summary statistics, two-sample tests, rank tests, generalised linear models, cumulative link models, Cox models, loglinear models, and general maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples. Variances by Taylor series linearisation or replicate weights. Post-stratification, calibration, and raking. Two-phase subsampling designs. Graphics. PPS sampling without replacement. Principal components, factor analysis.

svrVar: Compute variance from replicates

Description

Usage

Arguments

Value

See Also