... An alternative technique to resolve the multi-collinearity problem is to consider parameter estimation with priori available linear restrictions on the unknown parameters, which may be exact or stochastic. That is, in ...

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... the **logistic** **regression** **model** is due to its mathematical flexibility and in several medical applications it provides clinically meaningful in- terpretations (Hosmer and Lemeshow, ...the ...

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... for **logistic** **regression** models based on a measure of ...the **logistic** **regression** ...a **logistic** **regression** **model** supplies to the true ...probit **regression** with only ...

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... **Logistic** **Regression** has been used in the biological sciences in early twentieth ...A **logistic** **regression** **model** allows us to establish a relationship between a binary outcome variable ...

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... Most of the current studies on drunk driving accidents focus on law making and public education. However, especially in China, there is less statistical analysis on the severity of drunk driving accidents between driving ...

8

... D-optimal **model** was calculated for **logistic** **regression** **model** with three independent variables in a specific state, the idea of building locally optimal designs for **logistic** ...

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... statistical **model** for the analysis of its predictors for the case of Kebbi ...a **logistic** **regression** **model** using maximum likelihood estimation is ...the **model** using Kebbi State malaria ...

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... In this article, we propose a new estimator which is called the Stochastic Re- stricted Liu Estimator (SRLE) when the linear stochastic restrictions are available in addition to the **logistic** **regression** ...

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... two-classification **Logistic** **regression** **model** to carry out the study of haze weather in ...cumulative **logistic** **model** can be used to analyze and compare the probability of the occur- ...

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... First, we prove in Section 2 that the classical Maximum Likelihood estimator (ML) stays uniformly bounded if one adds outliers to the original sample. On the other hand, it is shown in Section 3 that the norm of the ...

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... Abstract: Term deposit is always an essential business of a bank and a good market campaign plays an essential role in financial selling. Nowadays, the telephone marketing, which can assist consulting institution to ...

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... on **logistic** **regression** **model**, and biomed- ical data usually contain confidential information about individuals [3] which should be treated ...

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... Zanzibar being Small Island with small economy in peripheral of Africa show no difference compared with other African countries. The analysis of 2009/2010 Zanzibar Household Budget Survey (ZHBS) is analogous to that of ...

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... binary **logistic** **regression** **model**, it is assumed that the relationship between the continuous independent variables and the logit (log odds) is ...binary **logistic** **regression** ...binary ...

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... for **logistic** **regression** models have been developed recently (Evans and Li ...assumed **logistic** **regression** **model** is embedded in a more general parametric family of models (Prentice ...

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... stepwise **logistic** **regression** was carried out to identify the factors which are jointly responsible for the successive level of the ...Stepwise **logistic** **regression** was carried out using forward ...

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... classical **logistic** **regression** **model**, and performed both parametric and non-parametric bootstrap for estimating confidence interval of parameters for logis- tic **model** and odds ...

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... the **logistic** **regression** curves for the three leakage current models are obtained in ...the **logistic** **regression** **model** for the three leakage current levels, which produced the simple ...

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... Multinomial **Logistic** **Regression** **model** which is one of the important methods for categorical data ...This **model** deals with one nominal/ordinal response variable that has more than two ...

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... Abstract. Security concerns have been raised since big data became a prominent tool in data analysis. For instance, many machine learning algorithms aim to generate prediction models using training data which contain ...

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