# fit_univariate: Fit Univariate Distribution In fitur: Fit Univariate Distributions

## Description

Fit Univariate Distribution

## Usage

 `1` ```fit_univariate(x, distribution, type = "continuous") ```

## Arguments

 `x` numeric vector `distribution` character name of distribution `type` discrete or continuous data

## Value

a fitted list object of d, p, q, r distribution functions and parameters, MLE for probability distributions, custom fit for empirical

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40``` ```# Fit Discrete Distribution set.seed(42) x <- rpois(1000, 3) fitted <- fit_univariate(x, 'pois', type = 'discrete') # density function plot(fitted\$dpois(x=0:10), xlab = 'x', ylab = 'dpois') # distribution function plot(fitted\$ppois(seq(0, 10, 1)), xlab= 'x', ylab = 'ppois') # quantile function plot(fitted\$qpois, xlab= 'x', ylab = 'qpois') # sample from theoretical distribution summary(fitted\$rpois(100)) # estimated parameters from MLE fitted\$parameters set.seed(24) x <- rweibull(1000, shape = .5, scale = 2) fitted <- fit_univariate(x, 'weibull') # density function plot(fitted\$dweibull, xlab = 'x', ylab = 'dweibull') # distribution function plot(fitted\$pweibull, xlab = 'x', ylab = 'pweibull') # quantile function plot(fitted\$qweibull, xlab = 'x', ylab = 'qweibull') # sample from theoretical distribution summary(fitted\$rweibull(100)) # estimated parameters from MLE fitted\$parameters ```

### Example output

```   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
0.00    1.00    3.00    2.75    4.00   10.00
lambda
2.93
Min.  1st Qu.   Median     Mean  3rd Qu.     Max.
0.00001  0.18442  1.18814  4.83963  5.18201 81.99765
shape     scale
0.4879054 2.0564428
```

fitur documentation built on Oct. 6, 2021, 5:06 p.m.