IceCast (version 2.1.0)

fit_weights: Compute weighting between two models

Description

Compute weighting between two models based on accuracy in predicting a set of observations. Computation is via the Expectation-Maximization algorithm.

Usage

fit_weights(mod1, mod2, obs, prop_area, w_ini = 0.5, z_ini = 0.5,
  eps = 0.01)

Arguments

mod1

array with estimated sea ice probability from model 1. Dimensions are nuumber of training years x lon x lat.

mod2

array with estimated sea ice probability from model 2. Dimensions are nuumber of training years x lon x lat.

obs

array with observations of sea ice presence (1) and absence (0). Dimensions are nuumber of training years x lon x lat.

prop_area

matrix that gives the proportion of area in each grid box. Should sum to 1. Dimensions are lon x lat.

w_ini

initial value of all w, defaults to 0.5.

z_ini

initial value of all z, defaults to 0.5.

eps

tolerance for EM algorithm to reach convergence, defaults to 0.01.

Value

value between 0 and 1 giving the weight on the first model

Examples

# NOT RUN {
weight <- fit_weights(mod1 = clim_9_2005_2007, mod2 = ppe_9_2005_2007,
obs = obs_9_2005_2007, prop_area = prop_area)
# }