---
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%"
)
```

# clust431

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

The goal of clust431 is to ...

## Installation

You can install the released version of clust431 from [CRAN](https://CRAN.R-project.org) with:

``` r
install.packages("clust431")
```

## Example

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

```{r example}
library(clust431)
## basic example code
```

What is special about using `README.Rmd` instead of just `README.md`? You can include R chunks like so:

```{r cars}
iris2 = iris[1:4,]
em_clust = function(k, data){
  ranmeans = rep(0, ncol(data))
  for (i in 1:(k-1)){
    ranmeans = rbind(ranmeans, ranmeans)
  }
  for (j in 1:k){
    for(i in 1:ncol(data)){
      maxval = max(data[,i])
      minval = min(data[,i])
      rand = runif(n=1, min=minval, max=maxval)
      ranmeans[j,i] = rand
    }
  }
  icluster = rep(0, nrow(data))
  list = rep(0, k)
  for (z in 1:nrow(data)){
    for (y in 1:k){
      list[y] = dmvnorm(data[z,], mean = ranmeans[y,], sigma = cov(data))
    }
    icluster[z] = which.max(list)
    list = rep(0, k)
  }
  print(icluster)
  means = rep(0,k)
  
  data = cbind(data, icluster)
  means = t(1:(ncol(data)-1))
  for (i in 1:(k-1)){
    means = rbind(means, means)
  }
  for (i in 1:k){
    means[i,] = colMeans(data[data[,ncol(data)] == i,])[-ncol(data)]
  }
  print(means)
  cluster = rep(0, nrow(data))
  list = rep(0, k)
  for (z in 1:nrow(data)){
    for (y in 1:k){
      list[y] = dmvnorm(data[z,-ncol(data)], mean = means[y,], sigma = cov(data[data[,ncol(data)] == y,-ncol(data)]))
    }
    cluster[z] = which.max(list)
    list = rep(0, k)
  }
  return(cluster)
}
em_clust(k=2, data=iris2)
```

You'll still need to render `README.Rmd` regularly, to keep `README.md` up-to-date.

You can also embed plots, for example:

```{r pressure, echo = FALSE}
plot(pressure)
```

In that case, don't forget to commit and push the resulting figure files, so they display on GitHub!