Estimation of Regional Sub-Daily Rainfall Ratios Using SKATER Algorithm and Logistic Regression

Abstract The present study proposes a climate change assessment tool based on a statistical downscaling (SD) approach for describing the linkage between large-scale climate predictors and observed daily rainfall characteristics at a local site. The proposed SD of the daily rainfall process (SDRain) model is based on a combination of a logistic regression model for representing the daily rainfall occurrences and a nonlinear regression model for describing the daily precipitation amounts. A scaling factor (SR) and correction coefficient (CR) are suggested to improve the accuracy of the SDRain model in representing the variance of the observed daily precipitation amounts in each month without affecting the monthly mean precipitation. SDRain facilitates the construction of daily precipitation models for the current and future climate conditions. The tool is tested using the National Center for Environmental Prediction re-analysis data and the observed daily precipitation data available for the 1961–2001 period at two study sites located in two completely different climatic regions: the Seoul station in subtropical-climate Korea and the Dorval Airport station in cold-climate Canada. Results of this illustrative application have indicated that the proposed functions (e.g. logistic regression, SR, and CR) contribute marked improvement in describing daily precipitation amounts and occurrences. Furthermore, the comparison analyses show that the proposed SD method could provide more accurate results than those given by the currently popular SDSM method.

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Identifying the dependency pattern of daily rainfall of Dhaka station in Bangladesh using Markov chain and logistic regression model

Agricultural Sciences ◽

10.4236/as.2012.33045 ◽

2012 ◽

Vol 03 (03) ◽

pp. 385-391 ◽

Cited By ~ 1

Author(s):

Mina Mahbub Hossain ◽

Sayedul Anam

Keyword(s):

Logistic Regression ◽

Markov Chain ◽

Regression Model ◽

Logistic Regression Model ◽

Daily Rainfall

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How Useful is the Power Law of Practice for Recognizing Practice in Concentration Tests?

European Journal of Psychological Assessment ◽

10.1027/1015-5759.23.3.157 ◽

2007 ◽

Vol 23 (3) ◽

pp. 157-165 ◽

Cited By ~ 4

Author(s):

Carmen Hagemeister

Keyword(s):

Logistic Regression ◽

Reaction Time ◽

Power Law ◽

Error Rate ◽

Reaction Times ◽

Practice Effect ◽

Practice Effects ◽

Rate Decrease ◽

Small Practice

Abstract. When concentration tests are completed repeatedly, reaction time and error rate decrease considerably, but the underlying ability does not improve. In order to overcome this validity problem this study aimed to test if the practice effect between tests and within tests can be useful in determining whether persons have already completed this test. The power law of practice postulates that practice effects are greater in unpracticed than in practiced persons. Two experiments were carried out in which the participants completed the same tests at the beginning and at the end of two test sessions set about 3 days apart. In both experiments, the logistic regression could indeed classify persons according to previous practice through the practice effect between the tests at the beginning and at the end of the session, and, less well but still significantly, through the practice effect within the first test of the session. Further analyses showed that the practice effects correlated more highly with the initial performance than was to be expected for mathematical reasons; typically persons with long reaction times have larger practice effects. Thus, small practice effects alone do not allow one to conclude that a person has worked on the test before.

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Perceived Effectiveness of Random Testing for Alcohol and Drugs in the Australian Aviation Community

Aviation Psychology and Applied Human Factors ◽

10.1027/2192-0923/a000031 ◽

2012 ◽

Vol 2 (2) ◽

pp. 72-81

Author(s):

Christina M. Rudin-Brown ◽

Eve Mitsopoulos-Rubens ◽

Michael G. Lenné

Keyword(s):

Logistic Regression ◽

Online Survey ◽

Random Testing ◽

Regression Analyses ◽

Perceived Effectiveness ◽

Student Pilots ◽

Alcohol And Drugs ◽

Positive Attitudes ◽

One Year ◽

Alcohol And Other Drugs

Random testing for alcohol and other drugs (AODs) in individuals who perform safety-sensitive activities as part of their aviation role was introduced in Australia in April 2009. One year later, an online survey (N = 2,226) was conducted to investigate attitudes, behaviors, and knowledge regarding random testing and to gauge perceptions regarding its effectiveness. Private, recreational, and student pilots were less likely than industry personnel to report being aware of the requirement (86.5% versus 97.1%), to have undergone testing (76.5% versus 96.1%), and to know of others who had undergone testing (39.9% versus 84.3%), and they had more positive attitudes toward random testing than industry personnel. However, logistic regression analyses indicated that random testing is more effective at deterring AOD use among industry personnel.

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