---
title: "Monte Carlo time series trend analysis"
author: "Alonso Arriagadada M.  <alonso.arriagada@usach.cl>"
date: "29-11-2023"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Monte Carlo time series trend analysis}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

R package to apply Monte Carlo time series trend analysis, based on Ricchetti (Ricchetti, 2018). It generates a dataframe with numerical results and a plot to visualize results.

## Requirements
Dependencies: trend, reshape2, ggplot2, magrittr, lmomco, dplyr

## Installation
You can install the development version of MCTrend from GitHub with this R command:
```{r setup,eval = FALSE}
# install.packages("remotes")
remotes::install_github("Alobondo/MCTrend")
library(MCTrend)
```

## Usage
Functions | Description |
--- | --- |
```MCTrend(x, n_rep, plot_title, int = 0.25, opt)``` | Apply Monte Carlo time series trend analysis. |

Parameters | Description |
--- | --- |
```x``` | A data frame containing the input data. The first row expected to contain model names or time series names.. |
```n_rep``` | Number of replications for the Monte Carlo simulation. |
```plot_title``` | Title for the plot. |
```int``` | Number indicating lower threshold value of the interval within which no trend is defined, the upper value is calculated based on this value, by default a lower value of 0.25 is considered. |
```opt``` | A number indicating type of results, for opt = 1 returns test result, opt = 2 returns plot. |

## File for example
To download a file with the reference format follow this path: https://github.com/Alobondo/Trend_and_Stationarity_Tests/raw/main/PP_T%26S_test.xlsx
