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adamhsparks merged 1 commit into from
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23 changes: 18 additions & 5 deletions README.Rmd
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ practice.

- Judgment post-stratified (JPS) sampling
- Ranked set sampling (RSS)
- Porbability-proportional to size (PPS) sampling
- Probability-proportional to size (PPS) sampling
- Spatially balanced sampling (SBS)
- Two-stage cluster sampling

Expand Down Expand Up @@ -82,7 +82,9 @@ Sampling is made following the diagram below.
Use the following code to install this package:

```{r, eval=F}
if (!require("remotes")) install.packages("remotes")
if (!require("remotes")) {
install.packages("remotes")
}
remotes::install_github("AAGI-AUS/InPlotSampling", upgrade = FALSE)
```

Expand Down Expand Up @@ -110,7 +112,14 @@ rhos <- rep(0.75, n_rankers)
taus <- sigma * sqrt(1 / rhos^2 - 1)
population <- qnorm((1:population_size) / (population_size + 1), mu, sigma)

data <- InPlotSampling::jps_sample(population, n, H, taus, n_rankers, with_replacement)
data <- InPlotSampling::jps_sample(
population,
n,
H,
taus,
n_rankers,
with_replacement
)
data <- data[order(data[, 2]), ]

InPlotSampling::rss_jps_estimate(
Expand Down Expand Up @@ -159,8 +168,12 @@ sample_id <- df_sample[, 1]
y_sample <- y[sample_id]

sbs_pps_estimates <- sbs_pps_estimate(
population, sample_sizes, y_sample, df_sample,
n_bootstrap = 100, alpha = 0.05
population,
sample_sizes,
y_sample,
df_sample,
n_bootstrap = 100,
alpha = 0.05
)
print(sbs_pps_estimates)
#> n1 n2 Estimate St.error 95% Confidence intervals
Expand Down
128 changes: 55 additions & 73 deletions README.md
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Original file line number Diff line number Diff line change
@@ -1,48 +1,54 @@
---
output: github_document
bibliography: inst/Reference.bib
nocite: |
@Ozturk2021
---

<!-- README.md is generated from README.Rmd. Please edit that file -->



# InPlotSampling



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has not yet been a stable, usable release suitable for the
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<br> [![minimal R
version](https://img.shields.io/badge/R%3E%3D-3.5.0-6666ff.svg)](https://cran.r-project.org/)
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<!-- badges: end -->

The InPlotSampling package provides a way for researchers to easily
implement these sampling methods in practice.
The InPlotSampling package provides a way for researchers to easily implement these sampling methods in
practice.

- Judgment post-stratified (JPS) sampling
- Ranked set sampling (RSS)
- Porbability-proportional to size (PPS) sampling
- Probability-proportional to size (PPS) sampling
- Spatially balanced sampling (SBS)
- Two-stage cluster sampling

## Table of Contents

<!-- vim-markdown-toc GFM -->

- [Sampling Methods](#sampling-methods)
- [JPS Sampling](#jps-sampling)
- [RSS](#rss-sampling)
- [Installation](#installation)
- [Examples](#examples)
- [JPS Sample and Estimator](#jps-sample-and-estimator)
- [SBS PPS Sample and Estimator](#sbs-pps-sample-and-estimator)
- [Citing this package](#citing-this-package)
- [Related Reference](#related-reference)
* [Sampling Methods](#sampling-methods)
* [JPS Sampling](#jps-sampling)
* [RSS](#rss-sampling)
* [Installation](#installation)
* [Examples](#examples)
* [JPS Sample and Estimator](#jps-sample-and-estimator)
* [SBS PPS Sample and Estimator](#sbs-pps-sample-and-estimator)
* [Citing this package](#citing-this-package)
* [Related Reference](#related-reference)

<!-- vim-markdown-toc -->

Expand All @@ -52,27 +58,23 @@ implement these sampling methods in practice.

Sampling is made following the diagram below.

<figure>
<img src="man/figures/jps-diagram.drawio.svg"
alt="JPS sampling diagram" />
<figcaption aria-hidden="true">JPS sampling diagram</figcaption>
</figure>
![JPS sampling diagram](man/figures/jps-diagram.drawio.svg)

### RSS

Sampling is made following the diagram below.

<figure>
<img src="man/figures/rss-diagram.drawio.svg" alt="RSS diagram" />
<figcaption aria-hidden="true">RSS diagram</figcaption>
</figure>
![RSS diagram](man/figures/rss-diagram.drawio.svg)

## Installation

Use the following code to install this package:


``` r
if (!require("remotes")) install.packages("remotes")
if (!require("remotes")) {
install.packages("remotes")
}
remotes::install_github("AAGI-AUS/InPlotSampling", upgrade = FALSE)
```

Expand All @@ -81,9 +83,7 @@ remotes::install_github("AAGI-AUS/InPlotSampling", upgrade = FALSE)
### JPS Sample and Estimator

<details>
<summary>
JPS sample and estimator
</summary>
<summary>JPS sample and estimator</summary>

``` r
set.seed(112)
Expand All @@ -102,7 +102,14 @@ rhos <- rep(0.75, n_rankers)
taus <- sigma * sqrt(1 / rhos^2 - 1)
population <- qnorm((1:population_size) / (population_size + 1), mu, sigma)

data <- InPlotSampling::jps_sample(population, n, H, taus, n_rankers, with_replacement)
data <- InPlotSampling::jps_sample(
population,
n,
H,
taus,
n_rankers,
with_replacement
)
data <- data[order(data[, 2]), ]

InPlotSampling::rss_jps_estimate(
Expand All @@ -122,15 +129,12 @@ InPlotSampling::rss_jps_estimate(
#> 5 SRS estimate 9.793 0.783 8.766,10.821
#> 6 Minimum 9.542 0.500 8.887,10.198
```

</details>

### SBS PPS Sample and Estimator

<details>
<summary>
SBS PPS sample and estimator
</summary>
<summary>SBS PPS sample and estimator</summary>

``` r
set.seed(112)
Expand All @@ -154,49 +158,27 @@ sample_id <- df_sample[, 1]
y_sample <- y[sample_id]

sbs_pps_estimates <- sbs_pps_estimate(
population, sample_sizes, y_sample, df_sample,
n_bootstrap = 100, alpha = 0.05
population,
sample_sizes,
y_sample,
df_sample,
n_bootstrap = 100,
alpha = 0.05
)
print(sbs_pps_estimates)
#> n1 n2 Estimate St.error 95% Confidence intervals
#> 1 5 5 2.849 0.1760682 2.451,3.247
```

</details>

# Citing this package

This package can be cited using `citation("InPlotSampling")` which
generates

To cite package 'InPlotSampling' in publications use:
This package can be cited using `citation("InPlotSampling")` which generates

Ozturk O, Rogers S, Kravchuk O, Kasprzak P (2021). _InPlotSampling:
Easing the Application of Ranked Set Sampling in Practice_. R package
version 0.1.0, <https://aagi-aus.github.io/InPlotSampling/>.

A BibTeX entry for LaTeX users is

@Manual{,
title = {InPlotSampling: Easing the Application of Ranked Set Sampling in Practice},
author = {Omer Ozturk and Sam Rogers and Olena Kravchuk and Peter Kasprzak},
year = {2021},
note = {R package version 0.1.0},
url = {https://aagi-aus.github.io/InPlotSampling/},
}
```
Error in `citation()`:
! there is no package called 'InPlotSampling'
```

# Related Reference

<div id="refs" class="references csl-bib-body hanging-indent"
entry-spacing="0">

<div id="ref-Ozturk2021" class="csl-entry">

Ozturk, Omer, and Olena Kravchuk. 2021. “Judgment Post-Stratified
Assessment Combining Ranking Information from Multiple Sources, with a
Field Phenotyping Example.” *Journal of Agricultural, Biological and
Environmental Statistics*. <https://doi.org/10.1007/s13253-021-00439-1>.

</div>

</div>
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