Title: | Small Area Estimation for Continuous Zero Inflated Data |
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Description: | Provides functionality to fit a zero-inflated estimator for small area estimation. This estimator is a combines a linear mixed effects regression model and a logistic mixed effects regression model via a two-stage modeling approach. The estimator's mean squared error is estimated via a parametric bootstrap method. Chandra and others (2012, <doi:10.1080/03610918.2011.598991>) introduce and describe this estimator and mean squared error estimator. White and others (2024+, <doi:10.48550/arXiv.2402.03263>) describe the applicability of this estimator to estimation of forest attributes and further assess the estimator's properties. |
Authors: | Josh Yamamoto [aut, cre], Dinan Elsyad [aut], Grayson White [aut], Julian Schmitt [aut], Niels Korsgaard [aut], Kelly McConville [aut], Kate Hu [aut] |
Maintainer: | Josh Yamamoto <[email protected]> |
License: | MIT + file LICENSE |
Version: | 0.2.0.9000 |
Built: | 2025-03-09 05:57:28 UTC |
Source: | https://github.com/harvard-ufds/saeczi |
FIA Population Level Auxiliary Data for Oregon
pop
pop
An object of class data.frame
with 10060 rows and 10 columns.
Fit a zero-inflation estimator.
saeczi( samp_dat, pop_dat, lin_formula, log_formula = lin_formula, domain_level, B = 100L, mse_est = FALSE, estimand = "means", parallel = FALSE, transform_fun = NULL, inv_transform_fun = NULL )
saeczi( samp_dat, pop_dat, lin_formula, log_formula = lin_formula, domain_level, B = 100L, mse_est = FALSE, estimand = "means", parallel = FALSE, transform_fun = NULL, inv_transform_fun = NULL )
samp_dat |
A data.frame with domains, auxiliary variables, and the response variable of a sample |
pop_dat |
A data.frame with domains and auxiliary variables of a population. |
lin_formula |
Formula. Specification of the response and fixed effects of the linear regression model |
log_formula |
Formula. Specification of the response and fixed effects of the logistic regression model |
domain_level |
String. The column name in samp_dat and pop_dat that encodes the domain level |
B |
Integer. The number of bootstraps to be used in MSE estimation. |
mse_est |
Logical. Whether or not MSE estimation should happen. |
estimand |
String. Whether the estimates should be 'totals' or 'means'. |
parallel |
Logical. Should the MSE estimation be computed in parallel. |
transform_fun |
Function. Function to be applied to the response variable prior to modeling. |
inv_transform_fun |
Function. Inverse of transform_fun. Required if transform_fun is specified. |
An object of class 'zi_mod' with defined 'print()' and 'summary()' methods. The object is structured like a list and contains the following elements:
* call: The original function call
* res: A data.frame containing the estimates and mse estimates
* lin_mod: The modeling object used to fit the original linear model
* log_mod: The modeling object used to fit the original logistic model
data(pop) data(samp) lin_formula <- DRYBIO_AG_TPA_live_ADJ ~ tcc16 + elev result <- saeczi(samp_dat = samp, pop_dat = pop, lin_formula = lin_formula, log_formula = lin_formula, domain_level = "COUNTYFIPS", mse_est = FALSE)
data(pop) data(samp) lin_formula <- DRYBIO_AG_TPA_live_ADJ ~ tcc16 + elev result <- saeczi(samp_dat = samp, pop_dat = pop, lin_formula = lin_formula, log_formula = lin_formula, domain_level = "COUNTYFIPS", mse_est = FALSE)
FIA sample data for Oregon
samp
samp
An object of class tbl_df
(inherits from tbl
, data.frame
) with 1494 rows and 11 columns.