Displays the fit of a linear, generalized linear, generalized additive or nonlinear model.

### Options

`PRINT` = string tokens |
What to print (`model, deviance, summary, estimates, correlations, fittedvalues, accumulated` , `confidence` ); default `mode,summ,esti` |
---|---|

`CHANNEL` = identifier |
Channel number of file, or identifier of a text to store output; default current output file |

`DENOMINATOR` = string token |
Whether to base ratios in accumulated summary on rms from model with smallest residual ss or smallest residual ms (`ss, ms` ); default `ss` |

`NOMESSAGE` = string tokens |
Which warning messages to suppress (`dispersion` , `leverage` , `residual` , `vertical` , `df` , `inflation` ); default `*` |

`FPROBABILITY` = string token |
Printing of probabilities for variance and deviance ratios (`yes, no` ); default `no` |

`TPROBABILITY` = string token |
Printing of probabilities for t-statistics (`yes, no` ); default `no` |

`SELECTION` = string tokens |
Statistics to be displayed in the summary of analysis produced by `PRINT=summary` , `seobservations` is relevant only for a Normally distributed response, and `%cv` only for a gamma-distributed response (`%variance` , `%ss` , `adjustedr2` , `r2` , `seobservations` , `dispersion` , `%cv` , `%meandeviance` , `%deviance` , `aic` , `bic` , `sic` ); default `%var` , `seob` if `DIST=normal` , `%cv` if `DIST=gamma` , and `disp` for other distributions |

`DISPERSION` = scalar |
Dispersion parameter to be used as estimate for variability in s.e.s; default is as set in the `MODEL` statement |

`RMETHOD` = string token |
Type of residuals to display (`deviance` , `Pearson` , `simple` ); default is as set in the `MODEL` statement |

`DMETHOD` = string token |
Basis of estimate of dispersion, if not fixed by `DISPERSION` option (`deviance, Pearson` ); default is as set in the `MODEL` statement |

`PROBABILITY` = scalar |
Probability level for confidence intervals for parameter estimates; default 0.95 |

`DFDISPERSION` = scalar |
allows you to specify the number of degrees of freedom for a dispersion parameter specified by the `DISPERSION` option; default is as set in the `MODEL` statement |

`SAVE` = identifier |
Specifies save structure of model to display; default `*` i.e. that from latest model fitted |

### No parameters

### Description

`RDISPLAY`

produces further output from a linear, generalized linear, generalized additive or nonlinear model. The `PRINT`

option has the same settings as in the `FIT`

directive, except that no monitoring is available. The `CHANNEL`

option selects the output channel to which the results are output, as in the `PRINT`

directive; this may be a text structure, allowing output to be stored prior to display. The `DENOMINATOR`

, `NOMESSAGE`

, `FPROBABILITY`

, `TPROBABILITY`

, `SELECTION`

and `PROBABILITY`

options are also as in the `FIT`

directive.

The `RMETHOD`

option allows you temporarily to change the method of forming residuals, for the output of the current statement only, in the same way as the corresponding option in the `MODEL`

directive sets the default method of formation. Similarly, the `DMETHOD`

option temporarily changes the method used to calculate the residual variability to be displayed for a generalized linear model, the `DISPERSION`

option allows you (temporarily) to set the dispersion parameter, and the `DFDISPERSION`

option allows you to define the number of degrees of freedom for a specified dispersion parameter. These again operate like the corresponding options of `MODEL`

(except that they apply only to the current statement).

The `SAVE`

option lets you specify the identifier of a regression save structure; the output will then relate to the most recent regression model fitted with that structure.

Options: `PRINT`

, `CHANNEL`

, `DENOMINATOR`

, `NOMESSAGE`

, `FPROBABILITY`

, `TPROBABILITY`

, `SELECTION`

, `DISPERSION`

, `RMETHOD`

, `DMETHOD`

, `PROBABILITY`

, `DFDISPERSION`

, `SAVE`

.

Parameters: none.

### See also

Directives: `MODEL`

, `FIT`

, `FITCURVE`

, `FITNONLINEAR`

, `PREDICT`

.

Procedures: `RCHECK`

, `RGRAPH`

, `RDESTIMATES`

, `RCOMPARISONS`

, `RTCOMPARISONS`

, `RWALD`

, `FIELLER`

, `RFUNCTION`

, `RDLOESSGROUPS`

.

Commands for: Regression analysis.

### Example

" Example FIT-1: Simple linear regression Modelling the relationship between counts of apples from 12 trees (recorded as 100s of fruit) and percentage damage by codling moth. (Snedecor & Cochran, Statistical analysis, 1980, p162.)" VARIATE [VALUES= 8, 6,11,22,14,17,18,24,19,23,26,40] Cropsize & [VALUES=59,58,56,53,50,45,43,42,39,38,30,27] Wormy DGRAPH Wormy; Cropsize " It is expected that the larger the crop is the less the damage will be, since the density of the flying moths is unrelated to the crop size. Try fitting a linear model relating the percentage of damage directly to the size of the crop." MODEL Wormy FIT Cropsize " Tree number 4 seems different from the rest: perhaps it was not adequately protected by the standard spraying programme, or was on the side from which the codling moths flew in to the orchard. Tree number 12 has a much larger crop than the rest: the results of the regression are strongly influenced by this one observation. Display all the fitted values, residuals and leverages (influence)." RDISPLAY [PRINT=fittedvalues] " Check the effect of omitting tree number 4." RESTRICT Wormy; .NOT.EXPAND(4; 12) FIT [PRINT=summary] Cropsize " Return to the complete dataset, and display the fitted line." RESTRICT Wormy FIT [PRINT=*] Cropsize RGRAPH [GRAPHICS=high] " Plot the fitted values against the residuals, to check that the variance is roughly constant; use the procedure RCHECK from the Genstat Procedure Library." RCHECK [GRAPHICS=high] residual; fittedvalues