Description Usage Arguments Details Value References See Also Examples

Fits a censored and shifted gamma EMOS model to a given training set.

1 2 | ```
fitMOScsg0(ensembleData, control = controlMOScsg0(),
exchangeable = NULL)
``` |

`ensembleData` |
An |

`control` |
A list of control values for the fitting functions specified via the function controlMOScsg0. For details and default values, see controlMOScsg0. |

`exchangeable` |
An optional numeric or character vector or factor indicating groups of
ensemble members that are exchangeable (indistinguishable).
The models have equal EMOS coefficients within each group.
If supplied, this argument will override any specification of
exchangeability in |

Given an ensemble of size *m*: *X_1, … , X_m*, the
following shifted gamma model left-censored at 0
is fit by `ensembleMOScsg0`

:

*Y ~ Gamma_0(κ,θ,q)*

where *Gamma_0* denotes the shifted gamma distribution left-censored at zero,
with shape *κ*, scale *θ* and shift *q*. The model is
parametrized such that the mean *κθ* is a linear function
*a + b_1 X_1 + … + b_m X_m*
of the ensemble forecats, and the variance *κθ^2* is a linear
function of the ensemble mean *c+d \overline{f}*, see Baran and Nemoda (2016)
for details.

`B`

is a vector of fitted regression coefficients: *b_1,
…, b_m*. Specifically, *a, b_1,…, b_m, c, d* are
fitted to optimize
`control$scoringRule`

over the specified training period using
`optim`

with `method = control$optimRule`

.

A list with the following output components:

`training` |
A list containing information on the training length and lag and the number of instances used for training for each modeling date. |

`a` |
A vector of fitted EMOS intercept parameters for each date. |

`B` |
A matrix of fitted EMOS coefficients for each date. |

`c,d` |
The fitted parameters for the variance, see details. |

`q` |
Fitted shift parameter, see details. |

M. Scheuerer and T. M. Hamill, Statistical post-processing of ensemble precipitation
forecasts by fitting censored, shifted gamma distributions.
*Monthly Weather Review* 143:4578–4596, 2015.

S. Baran and D. Nemoda, Censored and shifted gamma distribution based EMOS
model for probabilistic quantitative precipitation forecasting.
*Environmetrics* 27:280–292, 2016.

`controlMOScsg0`

,
`ensembleMOScsg0`

,

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
data("ensBMAtest", package = "ensembleBMA")
ensMemNames <- c("gfs","cmcg","eta","gasp","jma","ngps","tcwb","ukmo")
obs <- paste("PCP24","obs", sep = ".")
ens <- paste("PCP24", ensMemNames, sep = ".")
prcpTestData <- ensembleData(forecasts = ensBMAtest[,ens],
dates = ensBMAtest[,"vdate"],
observations = ensBMAtest[,obs],
station = ensBMAtest[,"station"],
forecastHour = 48,
initializationTime = "00")
prcpTrain <- trainingData(prcpTestData, trainingDays = 30,
date = "2008010100")
prcpTestFit <- fitMOScsg0(prcpTrain)
``` |

```
Loading required package: ensembleBMA
Loading required package: chron
Loading required package: evd
Attaching package: 'ensembleMOS'
The following objects are masked from 'package:ensembleBMA':
brierScore, cdf, crps, quantileForecast, trainingData
```

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