# Compute the Matrix of Weighted Predictions

### Description

Validates a community matrix and computes its associated weighted predictions matrix.

### Usage

1 | ```
weighted.predictions(CM, status=FALSE)
``` |

### Arguments

`CM` |
A valid community matrix. |

`status` |
Switches on an element-by-element progress indicator when set to |

### Details

The supplied matrix is validated as a community matrix, and a weighted predictions matrix is computed. This matrix is equivalent to the transposed community effect matrix with some ambiguous elements resolved using the value of the corresponding feedback matrix. Such values are represented enclosed in parentheses. In keeping with the paper by Levins, Dambacher and Rossignol (expression 42 in the paper cited below), the matrix orientation is congruent with the weighted feedback matrix, and transposed to the community effect matrix.

### Value

The weighted prediction matrix for a community matrix

### Author(s)

Alexis Dinno http://www.doyenne.com/LoopAnalyst/

### References

Dambacher, J. M., et al. (2003) Qualitative stability and ambiguity in model ecosystems. *The American Naturalist*, **161(6)**,876–888

Dambacher, J. M. and Li, H. W. and Rossignol, P. A. (2002) Relevance of community structure in assessing indeterminacy of ecological predictions. *Ecology*, **83(5)**,1372–1385

### See Also

`make.cem, make.wfm, make.adjoint, and make.T`

.

### Examples

1 2 3 4 5 | ```
## compute community effect matrix, and note high prevalence of ambiguous predictions
data(cm.dambacher)
make.cem(cm.dambacher, out=TRUE)
## compute weighted prediction matrix, and note disambiguation of the cem
weighted.predictions(t(cm.dambacher))
``` |

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