README.Rmd

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output: github_document
---

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```{r, include = FALSE}
knitr::opts_chunk$set(
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# bytd

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The aim of bytd is to provide a toolkit for fitting the Beta-Geometric/Negative-Binomial Distribution (BG/NBD) model for CLV Modeling.

## Installation

You can install the development version of bytd from [GitHub](https://github.com/) with:

``` r
# install.packages("pak")
pak::pak("vitormarquesr/bytd")
```

## Example

This is a basic example which shows you how to solve a common problem:

```{r example}
library(bytd)

# Simulating weekly RFM data for a base of 1300 customers
n <- 1300

# observation period of 80 weeks
T <- 80

# average purchase rate of twice per month
pars_gamma <- repar_Gamma(0.5, 0.3)

# average probability of droping out of 0.25.
pars_beta <- repar_Beta(0.25, 0.1)

rfm <- rbgnbd(n, T, pars_gamma[1], pars_gamma[2], pars_beta[1], pars_beta[2])

# fitting the marginalized loglikehood BG/NBD model throught a bayesian approach
m <- bgnbd(rfm, reff="marginal", approach="bayesian", cores=4)

m$fit
```