chartreview (version 1.0)

fullrun: Adaptive sampling algorithm which implements several types of sampling strategies

Description

Adaptive sampling algorithm which implements several types of sampling strategies

Usage

fullrun(
  dat1,
  S,
  dat2,
  mode = 1,
  batchsize = 100,
  raking = TRUE,
  rakingmode = 3,
  rakingthreshold = 0.05,
  sdEstimate = mad,
  minSamples = 10
)

Value

List with the resampled datasets per wave.

Arguments

dat1

First dataset on which the strata are computed.

S

Matrix defining the strata.

dat2

Second dataset on which confidence intervals are computed.

mode

Sampling mode (1 for random sampling, 2 for stratified random sampling, 3 for Neyman's sampling).

batchsize

Batch size in each wave.

raking

Boolean flag to switch on raking.

rakingmode

Option for raking (1 for random sampling, 2 for deterministic allocation, 3 for residual resampling).

rakingthreshold

Threshold for applying raking to a stratum.

sdEstimate

The estimate of the standard deviation as a function handle (usually sd or mad).

minSamples

Minimum number of samples used in each iteration.

References

.

Examples

require(chartreview)