Normal parameter estimates

`[___] = normfit(`

specifies whether each value in `x`

,`alpha`

,`censoring`

)`x`

is right-censored or not.
Use the logical vector `censoring`

in which 1 indicates
observations that are right-censored and 0 indicates observations that are fully
observed. With censoring, `muHat`

and
`sigmaHat`

are the maximum likelihood estimates
(MLEs).

To compute the confidence intervals, `normfit`

uses the exact
method for uncensored data and the Wald method for censored data. The exact method
provides exact coverage for uncensored samples based on *t* and
chi-square distributions.

`normfit`

is a function specific to normal distribution.
Statistics and Machine Learning Toolbox™ also offers the generic functions `mle`

, `fitdist`

, and `paramci`

and the **Distribution Fitter** app, which support various
probability distributions.

`mle`

returns MLEs and the confidence intervals of MLEs for the parameters of various probability distributions. You can specify the probability distribution name or a custom probability density function.Create a

`NormalDistribution`

probability distribution object by fitting the distribution to data using the`fitdist`

function or the**Distribution Fitter**app. The object properties`mu`

and`sigma`

store the parameter estimates. To obtain the confidence intervals for the parameter estimates, pass the object to`paramci`

.

[1] Evans, M., N. Hastings, and B. Peacock. *Statistical
Distributions*. 2nd ed. Hoboken, NJ: John Wiley & Sons, Inc., 1993.

[2] Lawless, J. F. *Statistical Models and Methods for Lifetime
Data*. Hoboken, NJ: Wiley-Interscience, 1982.

[3] Meeker, W. Q., and L. A. Escobar. *Statistical Methods for
Reliability Data*. Hoboken, NJ: John Wiley & Sons, Inc.,
1998.

Distribution Fitter | `NormalDistribution`

| `fitdist`

| `mle`

| `normcdf`

| `norminv`

| `normlike`

| `paramci`

| `statset`