# Ydiagnostics: Informative plots for Y and Yhat In expandFunctions: Feature Matrix Builder

## Description

This function presents diagnostic plots of estimate Yhat and response Y.

## Usage

 `1` ```Ydiagnostics(Y, Yhat, ...) ```

## Arguments

 `Y` R object representing response, coercible to a vector. `Yhat` R object representing estimate, coercible to a vector. The length of Y and Yhat must be equal. `...` Options for `cor` function. The defaults are use = "everything" and method = "pearson".

## Details

The plots shown are:

• Y vs Yhat. Under a perfect noise-free fitting, this would be a straight line with the points lined up on the red line, and the correlation wpuld be 1.0000.

• Y, Yhat and Y-Yhat (residual) time domain plots. The time steps are in samples.

• These show the ACF for the original Y, the residual, and |residual|. The latter helps identify nonlinearity in the residual.

## Value

Invisibly returns TRUE; this routine is only used for its graphical side effects described in Details.

`cor`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```# The order here looks backwards, but is chosen to # simulate a typical pair - Yhat will normally have # a smaller range than Y. set.seed(2) nObs <- 100 # Number of observations x <- stats::filter(rnorm(nObs),c(-0.99), method="recursive") x <- x + (x^2) # Nonlinear component myLags <- 0:2 X <- eTrim(eLag(x,myLags)) Y <- X[,+1,drop=FALSE] X <- X[,-1,drop=FALSE] lmObj <- lm(Y ~ X) Yhat <- predict(lmObj) Ydiagnostics(Y,Yhat) ```

### Example output   ```
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expandFunctions documentation built on May 2, 2019, 9:15 a.m.