README.Rmd

---
output: github_document
---

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

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# sinar

<!-- badges: start -->
<!-- badges: end -->

The goal of sinar is to implement the Conditional Least Square method for the Spatial non-negative Integer-valued Autoregressive $SINAR(1,1)$.

## Installation

You can install the development version from [GitHub](https://github.com/gilberto-sassi/) with:

``` r
# install.packages("devtools")
devtools::install_github("gilberto-sassi/sinar")
```
## Example: simulated case

```{r example}
library(sinar)

## Simulated data matrix from SINAR(1,1) with Poison(5) innovation
matrix_simulated <- sinar_pois(15, 15, 0.2, 0.2, 0.4, 5)

## Conditional Least Square (CLS) estimates
cls(matrix_simulated)

## Covariance matrix of CLS estimates
emp_cov(matrix_simulated)

```

## Example: real dataset (nematodoes)

```{r}
library(sinar)

## Nematodes counting datasets
data("nematodes")

## Conditional Least Square (CLS) estimates
cls(nematodes)

## Covariance matrix of CLS estimates
emp_cov(nematodes)

```

## Example: real dataset (carabidae)

```{r}
library(sinar)

## Carabidae counting dataset
data("carabidae")

## Conditional Least Square (CLS) estimates
cls(carabidae)

## Covariance matrix of CLS estimates
emp_cov(carabidae)

```