Pinned Repositories
ReliabilityDiagram
A package which provides the contigency table and all the other ingredients required to plot a reliability diagram. We also provide examples to show how this package could be used to create customized reliability diagrams based on user requirements.
Auto_Insurance
CRPS
A package to compute the Continuous Ranked Probability Score (crps) (Matheson and Winkler, 1976; Hersbach, 2000), the fair-crps (fcrps) (Ferro et al., 2008), and the adjusted-crps (acrps) (Ferro et al., 2008) given an ensemble prediction and an observation. The continuous ranked probability score is a negatively oriented score that is used to compare the empirical distribution of an ensemble prediction to a scalar observation. References: [1] Matheson, J. E. & Winkler, R. L. Scoring Rules for Continuous Probability Distributions. Management Science 22, 1087–1096 (1976). [2] Hersbach, H. Decomposition of the Continuous Ranked Probability Score for Ensemble Prediction Systems. Wea. Forecasting 15, 559–570 (2000). [3] Ferro, C. A. T., Richardson, D. S. & Weigel, A. P. On the effect of ensemble size on the discrete and continuous ranked probability scores. Meteorological Applications 15, 19–24 (2008).
gouthamnaveen.github.io
Naveen's website
mva
A python package to correct the bias of forecasts/hindcasts.
gouthamnaveen's Repositories
gouthamnaveen/CRPS
A package to compute the Continuous Ranked Probability Score (crps) (Matheson and Winkler, 1976; Hersbach, 2000), the fair-crps (fcrps) (Ferro et al., 2008), and the adjusted-crps (acrps) (Ferro et al., 2008) given an ensemble prediction and an observation. The continuous ranked probability score is a negatively oriented score that is used to compare the empirical distribution of an ensemble prediction to a scalar observation. References: [1] Matheson, J. E. & Winkler, R. L. Scoring Rules for Continuous Probability Distributions. Management Science 22, 1087–1096 (1976). [2] Hersbach, H. Decomposition of the Continuous Ranked Probability Score for Ensemble Prediction Systems. Wea. Forecasting 15, 559–570 (2000). [3] Ferro, C. A. T., Richardson, D. S. & Weigel, A. P. On the effect of ensemble size on the discrete and continuous ranked probability scores. Meteorological Applications 15, 19–24 (2008).
gouthamnaveen/mva
A python package to correct the bias of forecasts/hindcasts.
gouthamnaveen/Auto_Insurance
gouthamnaveen/gouthamnaveen.github.io
Naveen's website