MLRC2 | R Documentation |

Functions for reconstructing (predicting) environmental values from biological assemblages using Maximum Likelihood response Surfaces.

```
MLRC2(y, x, n.out=100, expand.grad=0.1, use.gam=FALSE, check.data=TRUE,
lean=FALSE, n.cut=5, verbose=TRUE, ...)
MLRC2.fit(y, x, n.out=100, expand.grad=0.1, use.gam=FALSE, check.data=TRUE,
lean=FALSE, n.cut=5, verbose=TRUE, ...)
## S3 method for class 'MLRC2'
predict(object, newdata=NULL, sse=FALSE, nboot=100,
match.data=TRUE, verbose=TRUE, ...)
## S3 method for class 'MLRC2'
performance(object, ...)
## S3 method for class 'MLRC2'
print(x, ...)
## S3 method for class 'MLRC2'
summary(object, full=FALSE, ...)
## S3 method for class 'MLRC2'
residuals(object, cv=FALSE, ...)
## S3 method for class 'MLRC2'
coef(object, ...)
## S3 method for class 'MLRC2'
fitted(object, ...)
```

`y` |
a data frame or matrix of biological abundance data. |

`x` , `object` |
a vector of environmental values to be modelled or an object of class |

`n.cut` |
cutoff value for number of occurrences. Species with fewer than n.cut occurrences will be excluded from the analysis. |

`n.out` |
to do |

`expand.grad` |
to do |

`use.gam` |
logical to use |

`newdata` |
new biological data to be predicted. |

`check.data` |
logical to perform simple checks on the input data. |

`match.data` |
logical indicate the function will match two species datasets by their column names. You should only set this to |

`lean` |
logical to exclude some output from the resulting models (used when cross-validating to speed calculations). |

`full` |
logical to show head and tail of output in summaries. |

`verbose` |
logical to show feedback during cross-validation. |

`nboot` |
number of bootstrap samples. |

`sse` |
logical indicating that sample specific errors should be calculated. |

`cv` |
logical to indicate model or cross-validation residuals. |

`...` |
additional arguments. |

Function `MLRC2`

Maximim likelihood reconstruction using 2D response curves.

Function `MLRC2`

returns an object of class `MLRC2`

with the following named elements:

Steve Juggins

Birks, H.J.B., Line, J.M., Juggins, S., Stevenson, A.C., & ter Braak, C.J.F. (1990) Diatoms and pH reconstruction. *Philosophical Transactions of the Royal Society of London*, **B, 327**, 263-278.

Juggins, S. (1992) Diatoms in the Thames Estuary, England: Ecology, Palaeoecology, and Salinity Transfer Function. *Bibliotheca Diatomologica*, **Band 25**, 216pp.

Oksanen, J., Laara, E., Huttunen, P., & Merilainen, J. (1990) Maximum likelihood prediction of lake acidity based on sedimented diatoms. *Journal of Vegetation Science*, **1**, 49-56.

ter Braak, C.J.F. & van Dam, H. (1989) Inferring pH from diatoms: a comparison of old and new calibration methods. *Hydrobiologia*, **178**, 209-223.

`WA`

, `MAT`

, `performance`

, and `compare.datasets`

for diagnostics.

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