crps_norm: CRPS for a Normal or a Mixture of two Normals
In JuGross/ensAR: Autoregressive postprocessing methods for ensemble forecasts

Description Usage Arguments Details Value Author(s) References Examples

Computes the continuous ranked probability score (CRPS) of given observations when the predictive distribution is the normal distribution or a mixture of two normals.

1	crps_norm(x, mu1, sd1, mu2 = mu1, sd2 = sd1, w1 = 1)

`x`	A vector of observations for which the CRPS is to be computed.
`mu1`	A vector of expectations of the first normal. Must be of the same length as `x`.
`sd1`	A vector of standard deviations of the first normal. Must be of the same length as `x`.
`mu2`	A vector of expectations of the second normal. Must be of the same length as `x`.
`sd2`	A vector of standard deviations of the second normal. Must be of the same length as `x`.
`w1`	A vector of weights between 0 and 1 associated with the first normal. Must be either of length one, or of the same length as `x`.

Formula (5) from Grimit et al. (2006) is applied for the special case of two normals.

A vector of CRPS values.

J. Gross, A. Moeller.

Grimit E.P., Gneiting T., Berrocal V., Johnson N.A. 2006. The continuous ranked probability score for circular variables and its application to mesoscale forecast ensemble verification. Quarterly Journal of the Royal Meteorological Society, 132, 2925–2942.