ratioEstimator {mase} | R Documentation |
Compute a ratio estimator
Description
Calculates a ratio estimator for a finite population mean/proportion or total based on sample data collected from a complex sampling design and auxiliary population data.
Usage
ratioEstimator(
y,
xsample,
xpop,
datatype = "raw",
pi = NULL,
N = NULL,
pi2 = NULL,
var_est = FALSE,
var_method = "LinHB",
B = 1000,
fpc = TRUE,
messages = TRUE
)
Arguments
y |
A numeric vector of the sampled response variable. |
xsample |
A numeric vector of the sampled auxiliary variable. |
xpop |
A numeric vector of population level auxiliary information. Must come in the form of raw data, population total or population mean. |
datatype |
A string that specifies the form of population auxiliary data. The possible values are "raw", "total" or "mean". If datatype = "raw", then xpop must contain a numeric vector of the auxiliary variable for each unit in the population. If datatype = "total" or "mean", then contains either the population total or population mean for the auxiliary 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. |
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.
References
Cochran W~G (1977). Sampling Techniques, 3rd edition. John Wiley & Sons, New York. Sarndal C~E, Swensson B, Wretman J (1992). Model Assisted Survey Sampling. Springer-Verlag, New York.
Examples
library(dplyr)
data(IdahoPop)
data(IdahoSamp)
xsample <- filter(IdahoSamp, COUNTYFIPS == "16055")
xpop <- filter(IdahoPop, COUNTYFIPS == "16055")
ratioEstimator(y = xsample$BA_TPA_ADJ,
xsample = xsample$tcc,
xpop = xpop$tcc,
datatype = "means",
N = xpop$npixels)