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---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# gpbStat
<!-- badges: start -->
[](https://cran.r-project.org/package=gpbStat)
[](https://cran.r-project.org/web/checks/check_results_gpbStat.html)
[](https://lifecycle.r-lib.org/articles/stages.html#stable-1)

[](https://cran.r-project.org/package=gpbStat)
<!-- badges: end -->
The package is used for statistical analysis of Plant Breeding experiments.
Package Website https://nandp1.github.io/gpbStat/
Note: In the latest version 0.3.1 estimation of Kings Variance is not included.
## Installation
Install latest package from Github through
``` r
install.packages("devtools")
library(devtools)
install_github("nandp1/gpbStat")
```
Install gpbStat from [CRAN](https://CRAN.R-project.org) with:
``` r
install.packages("gpbStat")
```
## Example
Line by Tester analysis (only crosses).
```{r example}
# Loading the gpbStat package
library(gpbStat)
# Loading dataset
data(rcbdltc)
## Now by using function ltc we analyze the data.
## The first parameter of `ltc` function is "data" followed by replication, line, tester and dependent variable(yield)
results1 = ltc(rcbdltc, replication, line, tester, yield)
## Viewing the results
results1
```
```{r}
# Similarly we analyze the line tester data containing only crosses laid out in Alpha lattice design.
# Load the package
library(gpbStat)
# Loading dataset
data("alphaltc")
# Viewing the Structure of dataset
str(alphaltc)
# There are five columns replication, block, line, tester and yield.
## Now by using function ltc we analyze the data.
## The first parameter of `ltc` function is "data" followed by replication, line, tester, dependent variable(yield) and block.
## Note: The "block" parameter comes at the end.
results2 = ltc(alphaltc, replication, line, tester, yield, block)
## Viewing the results
results2
```
```{r}
# Line x Tester analysis for multiple traits laid in Alpha lattice design.
# Load the package
library(gpbStat)
#Load the dataset
data("alphaltcmt")
# View the structure of dataframe.
str(alphaltcmt)
# Conduct Line x Tester analysis
result3 = ltcmt(alphaltcmt, replication, line, tester, alphaltcmt[,5:7], block)
# View the output
result3
```