نتایج جستجو برای: binary logistic model
تعداد نتایج: 2266426 فیلتر نتایج به سال:
medical compounds, especially antibiotics, in which remains in milk and dairy products on the one hand causes health problems such as allergic reactions and development of bacterial resistance to antibiotics are a serious threat to the health of consumers , and on the other hand, industrial troubles such as failure to produce fermented products can cause the milk back to the rancher. the purpos...
medical compounds, especially antibiotics, in which remains in milk and dairy products on the one hand causes health problems such as allergic reactions and Development of bacterial resistance to antibiotics are a serious threat to the health of consumers , and on the other hand, industrial troubles such as failure to produce fermented products can cause the milk back to the rancher. The purpos...
in a structural time series regression model, binary variables have been used to quantify qualitative or categorical quantitative events such as politic and economic structural breaks, regions, age groups and etc. the use of the binary dummy variables is not reasonable because the effect of an event decreases (increases) gradually over time not at once. the simple and basic idea in this paper i...
medical compounds, especially antibiotics, in which remains in milk and dairy products on the one hand causes health problems such as allergic reactions and Development of bacterial resistance to antibiotics are a serious threat to the health of consumers , and on the other hand, industrial troubles such as failure to produce fermented products can cause the milk back to the rancher. The purpos...
Background and purpose: To analyze the data in which the correlation between observations are to be considered, a general method is using marginal model with repeated measures, yet there is another method called conditional model with random clusters. Âccording to the binary responses, the aim of the present study is to compare the efficiency of these two models in studying the risk factors a...
We propose an online binary classification procedure for cases when there is uncertainty about the model to use and parameters within a model change over time. We account for model uncertainty through dynamic model averaging, a dynamic extension of Bayesian model averaging in which posterior model probabilities may also change with time. We apply a state-space model to the parameters of each mo...
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