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Estimate remaining useful life for a test component

The `predictRUL`

function estimates the remaining useful
life (RUL) of a test component given an estimation model and information about its usage
time and degradation profile. Before predicting the RUL, you must first configure your
estimation model using historical data regarding the health of an ensemble of similar
components, such as multiple machines manufactured to the same specifications. To do so,
use the `fit`

function.

Using `predictRUL`

, you can estimate the remaining useful life for
the following types of estimation models:

Degradation models

Survival models

Similarity models

For a basic example illustrating RUL prediction, see Update RUL Prediction as Data Arrives.

For general information on predicting remaining useful life using these models, see RUL Estimation Using RUL Estimator Models.

`estRUL = predictRUL(mdl,data)`

`estRUL = predictRUL(mdl,data,bounds)`

`estRUL = predictRUL(mdl,threshold)`

`estRUL = predictRUL(mdl,usageTime)`

`estRUL = predictRUL(mdl,covariates)`

`estRUL = predictRUL(___,Name,Value)`

`[estRUL,ciRUL] = predictRUL(___)`

`[estRUL,ciRUL,pdfRUL] = predictRUL(___)`

`[estRUL,ciRUL,pdfRUL,histRUL] = predictRUL(___)`

estimates the RUL of a component using covariate survival model
`estRUL`

= predictRUL(`mdl`

,`covariates`

)`mdl`

and the current covariate values for the
component.

specifies additional options using one or more name-value pair arguments.`estRUL`

= predictRUL(___,`Name,Value`

)