# intervals: Calculate fire intervals from a 'composite' In burnr: Forest Fire History Analysis

## Description

Calculate fire intervals from a `composite`

## Usage

 `1` ```intervals(comp, densfun = "weibull") ```

## Arguments

 `comp` A `composite` instance, usually output from `composite()`. Should contain only one series. `densfun` String giving desired distribution to fit. Either "weibull" or "lognormal". Default is "weibull".

## Value

An `intervals` object. `intervals` have components:

• "intervals" an integer vector giving the actual fire intervals.

• "fitdistr" a `fitdistr` object from `MASS::fitdistr()` representing the density function fit.

• "densfun" a string giving the name of the density function used.

• "kstest" an `htest` object from `stats::ks.test()` giving the result of a one-sample Kolmogorov-Smirnov test.

• "shapirotest" an `htest` object from `stats::shapiro.test()` giving the result of a Shapiro-Wilk normality test.

• "comp_name" a string giving the name of the interval's input composite.

• "event_range" an integer vector giving the year range (min, max) of events used to create this intervals.

• `composite()` to create a `composite` object.

• `mean.intervals()` gets mean fire interval.

• `median.intervals()` gets median fire interval.

• `quantile.intervals()` get fit distribution quantiles.

• `plot_intervals_dist()` plots `intervals`.

• `min.intervals()` gives the minimum fire interval.

• `max.intervals()` gives the maximum fire interval.

• `print.intervals()` prints common fire-interval summary statistics.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13``` ```data(pgm) interv <- intervals(composite(pgm)) print(interv) mean(interv) # Mean interval # Now fit log-normal distribution instead of Weibull. intervals(composite(pgm), densfun = "lognormal") ## Not run: # Boxplot of fire interval distribution. boxplot(intervals(composite(pgm))\$intervals) ## End(Not run) ```

burnr documentation built on March 10, 2021, 5:07 p.m.