| Type: | Package |
| Title: | Efficiency of Cluster Sampling for Crop Surveys |
| Version: | 0.1.0 |
| Author: | 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 <jeelani.miqbal@gmail.com> |
| 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>. |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| Imports: | stats, dplyr |
| RoxygenNote: | 7.2.1 |
| Depends: | R (≥ 2.10) |
| NeedsCompilation: | no |
| Packaged: | 2023-11-07 16:39:25 UTC; YEASIN |
| Repository: | CRAN |
| Date/Publication: | 2023-11-07 19:40:05 UTC |
Efficiency of Cluster Sampling for Crop Surveys
Description
Efficiency of Cluster Sampling for Crop Surveys
Usage
ImCluster(x, N = NULL)
Arguments
x |
Datasets |
N |
Number of clusters |
Value
results: Results
References
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
Examples
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)