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Probability plots

`probplot(y)`

`probplot(dist,y)`

`probplot(y,cens)`

`probplot(y,cens,freq)`

`probplot(dist,___)`

`probplot(ax,y)`

`probplot(ax,pd)`

`probplot(ax,fun,params)`

`probplot(___,'noref')`

`h = probplot(___)`

`probplot(`

creates a normal
probability plot comparing the distribution of the data in
`y`

)`y`

to the normal distribution. The plot includes a
reference line useful for judging whether the data follows a normal
distribution.

`probplot(`

creates a probability plot for the distribution specified by
`dist`

,___)`dist`

, using any of the previous syntaxes.

`probplot(___,'noref')`

omits the reference
line from the plot.

`probplot`

matches the quantiles of sample data to the quantiles of
a given probability distribution. The sample data is sorted, scaled according to the
choice of `dist`

, and plotted on the x-axis. When
`dist`

is `'lognormal'`

,
`'loglogistic'`

, or `'weibull'`

, the scaling is
logarithmic. Otherwise, the scaling is linear. The y-axis represents the quantiles of
the distribution specified in `dist`

, converted into probability
values. The scaling depends on the given distribution and is not linear.

Where the x-axis value is the *i*th sorted value from a sample of
size *N*, the y-axis value is the midpoint between evaluation points of
the empirical cumulative distribution function of the data. In the case of uncensored
data, the midpoint is equal to $$\frac{\left(i-0.5\right)}{N}$$.

`probplot`

superimposes a reference line to assess the linearity of
the plot. If the data is uncensored, then the line goes through the first and third
quartiles of the data, unless `dist`

is ```
'half
normal'
```

. If `dist`

is `'half normal'`

,
then `probplot`

uses the zeroth and second quartiles instead. If the
data is censored, then the line shifts accordingly.

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