summary.mat {analogue} | R Documentation |

## Summarise Modern Analogue Technique models

### Description

`summary`

method for class `"mat"`

.

### Usage

```
## S3 method for class 'mat'
summary(object, k = 10,
digits = max(2, getOption("digits") - 4), ...)
```

### Arguments

`object` |
an object of class |

`k` |
numeric; maximum modern analogues to use to summarise model fits. |

`digits` |
numeric; the number of significant digits with which to format results. |

`...` |
arguments passed to or from other methods. |

### Value

A list with the components below. The number of analogues used,
*k* is returned as attribute `"k"`

.

`summ` |
a data.frame containing the model fits for training set samples. See notes below. |

`tbl` |
matrix of summary statistics for an un-weighted model. |

`tbl.W` |
matrix of summary statistics for a weighted model. |

`call` |
the matched function call |

`quantiles` |
the quantiles of the distribution of pairwise
dissimilarities for the training set, for |

### Note

The returned component `"summ"`

contains the following:

- Obs:
the observed responses for the training set samples.

- Est:
the fitted values of the response for training set samples based on the average of

*k*-closest analogues.- Resi:
the residuals of the fitted model based on the average of

*k*-closest analogues.- W.Est:
the fitted values of the response for training set samples based on the weighted average of

*k*-closest analogues.- W.Resi:
the residuals of the fitted model based on the weighted average of

*k*-closest analogues.- minDC:
dissimilarity of closest analogue in training set for each training set sample.

- minResi:
smallest residual for an un-weighted model of size

`"k"`

.- k:
size of model leading to minimal residual,

`"minResi"`

.- minW.Resi:
smallest residual for a weighted model of size

`"k.W"`

.- k.W:
size of model leading to minimal residual,

`"minW.Resi"`

.

### Author(s)

Gavin L. Simpson

### See Also

### Examples

```
## Not run:
## continue the RLGH example from ?join
example(join)
## fit the MAT model using the squared chord distance measure
swap.mat <- mat(swapdiat, swappH, method = "SQchord")
swap.mat
## model summary
summary(swap.mat)
## model summary - evaluating models using k = 1, ..., 20
## analogues instead of the default, 10.
summary(swap.mat, k = 20)
## End(Not run)
```

*analogue*version 0.17-6 Index]