mase (version 0.1.5.2)

gregTree: Compute a regression tree estimator

Description

Calculates a regression tree estimator for a finite population mean/proportion or total based on sample data collected from a complex sampling design and auxiliary population data.

Usage

gregTree(
  y,
  xsample,
  xpop,
  pi = NULL,
  pi2 = NULL,
  var_est = FALSE,
  var_method = "LinHB",
  B = 1000,
  pval = 0.05,
  perm_reps = 500,
  bin_size = NULL,
  fpc = TRUE,
  messages = TRUE
)

Value

A list of output containing:

* pop_total: Estimate of population total.

* pop_mean: Estimate of the population mean (or proportion).

* weights: Survey weights produced by gregTree.

* 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.

xsample

A data frame of the auxiliary data in the sample.

xpop

A data frame of population level auxiliary information. It must contain the same names as xsample. If datatype = "raw", must contain unit level data. If datatype = "totals" or "means", then contains one row of aggregated, population totals or means for the auxiliary data. Default is "raw".

pi

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

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.

pval

Designated p-value level to reject null hypothesis in permutation test used to fit the regression tree. Default value is 0.05.

perm_reps

An integer specifying the number of permutations for each permutation test run to fit the regression tree. Default value is 500.

bin_size

A integer specifying the minimum number of observations in each node.

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

mcc17bmase

Examples

library(dplyr)
data(IdahoPop)
data(IdahoSamp)

xsample <- filter(IdahoSamp, COUNTYFIPS == "16055") 
xpop <- filter(IdahoSamp, COUNTYFIPS == "16055")

gregTree(y = xsample$BA_TPA_ADJ,
         xsample = xsample[c("tcc", "elev")],
         xpop = xpop[c("tcc", "elev")],
         var_est = TRUE)