| Title: | Efficiency of Cluster Sampling for Crop Surveys |
|---|---|
| Description: | Cluster sampling is a valuable approach when constructing a comprehensive list of individual units is challenging. It provides operational and cost advantages. This package is designed to test the efficiency of cluster sampling in terms cluster variance and design effect in context to crop surveys. This package has been developed using the algorithm of Iqbal et al. (2018) <doi:10.19080/BBOAJ.2018.05.555673>. |
| Authors: | M. Iqbal Jeelani [aut, cre], Fehim Jeelani [aut], Shakeel Ahmad Mir [aut], Showkat Maqbool [aut], Syed Naseem Geelani [aut], Mushtaq Ahmad Lone [aut], Md Yeasin [aut] |
| Maintainer: | M. Iqbal Jeelani <[email protected]> |
| License: | GPL-3 |
| Version: | 0.1.0 |
| Built: | 2025-03-02 02:47:36 UTC |
| Source: | https://github.com/cran/ImCluster |
Efficiency of Cluster Sampling for Crop Surveys
ImCluster(x, N = NULL)ImCluster(x, N = NULL)
x |
Datasets |
N |
Number of clusters |
results: Results
Iqbal, J. M., Faizan, D and Mansha, G. (2018) . A Review on the Recent Development on the Cluster Sampling. Biostatistics and Biometrics. 5(5): 555673. DOI: 10.19080/BBOAJ.2018.05.555673
N_clusters <- 105 orchards_per_cluster <- 4 data <- matrix(rnorm(N_clusters * orchards_per_cluster), nrow = orchards_per_cluster, byrow = TRUE) colnames(data) <- paste0("Cluster_", 1:N_clusters) demo_data <- data.frame(data) result_imcluster <- ImCluster(demo_data, N_clusters)N_clusters <- 105 orchards_per_cluster <- 4 data <- matrix(rnorm(N_clusters * orchards_per_cluster), nrow = orchards_per_cluster, byrow = TRUE) colnames(data) <- paste0("Cluster_", 1:N_clusters) demo_data <- data.frame(data) result_imcluster <- ImCluster(demo_data, N_clusters)