SPI-based drought category prediction using loglinear models

SPI-based Regional Drought Prediction Using Weighted Markov Chain Model

Drought is one of the most serious natural disasters in China. Drought disasters occur frequently and caused huge economic loss in recently. In this paper, a drought prediction model based on weighted Markov Chain is put forward. An application is demonstrated by Anhui province of Huaihe River in China. Based on the precipitation data during 1958-2006 at monthly scale, the different time scales...

Using the SPI to Identify Drought

Learning Verbal Transitivity Using LogLinear Models

Portuguese dictionaries lack information about the kind of phrases or clauses a verb goes with. In this paper we describe how this information can be computationally learned from an automatically tagged corpus with almost 10,000,000 words. Loglinear modeling for categorical data will be used to analyze and automatically identify the subcatego-rization dependencies. Loglinear models were also us...

Links between Binary and Multi-category Logit Item Response Models and Quasi-symmetric Loglinear Models – 443 –

— Caussinus’s loglinear model of quasi symmetry has interesting connections with models for within-subject effects with repeated categorical measurement. For binary responses, Tjur (1982) showed that estimates of main effect parameters in the quasi-symmetry model are also conditional maximum likelihood estimates of item parameters for a fixed effects treatment of subject terms in the Rasch item...

Links Between Binary and Multi-Category Logit Item Response Models and Quasi-Symmetric Loglinear Models

Caussinus’s loglinear model of quasi symmetry has interesting connections with models for within-subject effects with repeated categorical measurement. For binary responses, Tjur (1982) showed that estimates of main effect parameters in the quasi-symmetry model are also conditional maximum likelihood estimates of item parameters for a fixed effects treatment of subject terms in the Rasch item r...