A synthetic panel dataset containing 42 domains observed over 5 time periods
(2022 to 2026, total 210 observations). Features multiple response variables
representing various probability distributions (Gaussian, Poisson, Binomial,
Beta, Negative Binomial, and Gamma) driven by domain-level spatial autocorrelation
and first-order autoregressive AR(1) temporal dynamics. It shares the 42-domain
spatial structure of mys_proxmat and is formatted in domain-major order
for direct use in eblup_stfh.
Usage
data(sim_panel)Format
A data frame with 210 rows and 15 variables in domain-major order:
- area
Integer domain identifier (1 to 42).
- year
Year of observation (2022 to 2026).
- x1
Dynamic explanatory covariate with spatial & temporal variation.
- x2
Dynamic uniform explanatory covariate.
- y_gaussian
Gaussian direct estimator response with unsampled domains as NA.
- vardir
Direct sampling variance for Gaussian Fay-Herriot model.
- y_poisson
Count response (Poisson) with unsampled domains as NA.
- exposure
Expected population count / exposure offset for Poisson model.
- y_binomial
Number of successes (Binomial) with unsampled domains as NA.
- trials
Sample size / number of trials for Binomial model.
- y_beta
Continuous proportion response in (0, 1) for Beta regression.
- y_nbinomial
Overdispersed count response for Negative Binomial model.
- y_gamma
Skewed positive continuous response for Gamma regression.
- x_coord
Centroid x coordinate.
- y_coord
Centroid y coordinate.
Source
Simulated using sim_series_data based on the spatial
proximity structure of mys_proxmat.
Examples
data(sim_panel)
head(sim_panel)
#> area year x1 x2 y_gaussian vardir y_poisson exposure y_binomial
#> 1 1 2022 1.0967 2.6650 0.1591 0.04717 268 332 84
#> 2 1 2023 1.3387 2.7798 NA 0.15793 NA 363 NA
#> 3 1 2024 1.3375 2.3328 1.2971 0.06945 164 178 99
#> 4 1 2025 1.8651 2.1846 1.8610 0.04719 671 406 76
#> 5 1 2026 1.7945 2.6695 1.9166 0.10708 496 350 52
#> 6 2 2022 2.3614 2.2745 NA 0.11363 NA 258 NA
#> trials y_beta y_nbinomial y_gamma x_coord y_coord
#> 1 246 0.26165 2 1.8890 0.0354 0.2881
#> 2 126 NA NA NA 0.0354 0.2881
#> 3 239 0.30555 9 0.6434 0.0354 0.2881
#> 4 115 0.80090 73 3.1109 0.0354 0.2881
#> 5 73 0.47064 59 2.3906 0.0354 0.2881
#> 6 108 NA NA NA -0.2697 0.0128