mase (version 0.1.5.2)

horvitzThompson: Compute the Horvitz-Thompson Estimator

Description

Calculate the Horvitz-Thompson Estimator for a finite population mean/proportion or total based on sample data collected from a complex sampling design.

Usage

horvitzThompson(
  y,
  pi = NULL,
  N = NULL,
  pi2 = NULL,
  var_est = FALSE,
  var_method = "LinHB",
  B = 1000,
  fpc = TRUE,
  messages = TRUE
)

Value

List of output containing:

* pop_total: Estimate of population total.

* pop_mean: Estimate of population mean.

* pop_total_var: Estimated variance of population total estimate.

* pop_mean_var: Estimated variance of population mean estimate.

Arguments

y

A numeric vector of the sampled response variable.

pi

A numeric vector of inclusion probabilities for each sampled unit in y. If NULL, then simple random sampling without replacement is assumed.

N

A numeric value of the population size. If NULL, it is estimated with the sum of the inverse of the pis.

pi2

A square matrix of the joint inclusion probabilities. Needed for the "LinHT" variance estimator.

var_est

A logical indicating whether or not to compute a variance estimator. Default is FALSE.

var_method

The method to use when computing the variance estimator. Options are a Taylor linearized technique: "LinHB"= Hajek-Berger estimator, "LinHH" = Hansen-Hurwitz estimator, "LinHTSRS" = Horvitz-Thompson estimator under simple random sampling without replacement, and "LinHT" = Horvitz-Thompson estimator or a resampling technique: "bootstrapSRS" = bootstrap variance estimator under simple random sampling without replacement. The default is "LinHB".

B

The number of bootstrap samples if computing the bootstrap variance estimator. Default is 1000.

fpc

Default to TRUE, logical for whether or not the variance calculation should include a finite population correction when calculating the "LinHTSRS" or the "SRSbootstrap" variance estimator.

messages

A logical indicating whether to output the messages internal to mase. Default is TRUE.

References

hor52mase

Examples

library(dplyr)
data(IdahoSamp)
data(IdahoPop)
xsample <- filter(IdahoSamp, COUNTYFIPS == "16055")
xpop <- filter(IdahoPop, COUNTYFIPS == "16055") 

horvitzThompson(y = xsample$BA_TPA_ADJ,
                N = xpop$npixels,
                var_est = TRUE,
                var_method = "LinHTSRS")