Wyniki wyszukiwania

Sortuj według:

Ogranicz wyniki do:

Artykuł dostępny w postaci pełnego tekstu - kliknij by otworzyć plik

Application of the Rasch model in categorical pedigree analysis using MCEM: I binary data

100%

Qian G., Huggins R., Loesch D.

Discussiones Mathematicae Probability and Statistics

2004

tom 24

nr 2

255-280

An extension of the Rasch model with correlated latent variables is proposed to model correlated binary data within families. The latent variables have the classical correlation structure of Fisher (1918) and the model parameters thus have genetic interpretations. The proposed model is fitted to data using a hybrid of the Metropolis-Hastings algorithm and the MCEM modification of the EM-algorithm and is illustrated using genotype-phenotype data on a psychological subtest in families where some members are affected by the genetic disorder fragile X. In addition, hypothesis testing and model selection methods based on the Wald statistic are discussed.

Seasonal forecasting of tropical cyclone activity in the Australian and the South Pacific Ocean regions

76%

Wijnands J. S., Qian G., Shelton K. L., Fawcett R. J. B., Chan J. C. L., Kuleshov Y.

Mathematics of Climate and Weather Forecasting

2015

tom 1

nr 1

The Australian Bureau of Meteorology (Bureau) issues operational tropical cyclone (TC) seasonal forecasts for the Australian region (AR) and the South Pacific Ocean (SPO) and subregions therein. The forecasts are issued in October, ahead of the Southern Hemisphere TC season (November to April). Improvement of operational TC seasonal forecasts can lead to more accurate warnings for coastal communities to prepare for TC hazards. This study investigates the use of support vector regression (SVR) models, exploring new explanatory variables and non-linear relationships between them, the use of model averaging, and lastly the integration of forecast intervals based on a bias-corrected and accelerated non-parametric bootstrap. Hindcasting analyses show that the SVR model outperforms several benchmark methods. Analysis of the generated models shows that the Dipole Mode Index, 5VAR index and the Southern Oscillation Index are the most frequently selected as explanatory variables for TC seasonal forecasting in all regions. The usage of ENSOrelated covariates implies that definitions of regions and subregions may have to be updated to achieve optimal forecasting performance. Overall, the new SVR methodology is an improvement over the current linear discriminant analysis models and has the potential to increase accuracy of TC seasonal forecasts in the AR and SPO.

Ograniczanie wyników

1 Discussiones Mathematicae Probability and Statistics

1 Mathematics of Climate and Weather Forecasting

2 Qian G.

1 Chan J. C. L.

1 Fawcett R. J. B.

1 Huggins R.

1 Kuleshov Y.

1 Loesch D.

1 Shelton K. L.

1 Wijnands J. S.

1 2015

1 2004

Wyniki wyszukiwania

Application of the Rasch model in categorical pedigree analysis using MCEM: I binary data

Seasonal forecasting of tropical cyclone activity in the Australian and the South Pacific Ocean regions