logistic regression model
Stochastic Restricted Maximum Likelihood Estimator in Logistic Regression Model
... 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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On modified skew logistic regression model and its applications
... 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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Goodness of fit for the logistic regression model using relative belief
... 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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A Statistical Analysis Of Migration Using Logistic Regression Model
... 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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Research on the Drunk Driving Traffic Accidents Based on Logistic Regression Model
... 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 ...
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D-Optimal Design for Logistic Regression Model with Three Independent Variables
... 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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An Investigation of Malaria Predictors Using Logistic Regression Model
... 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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A New Stochastic Restricted Liu Estimator for the Logistic Regression Model
... 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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Study on Probability Estimation of Haze in Beijing Based Logistic Regression Model
... 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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The breakdown behavior of the maximum likelihood estimator in the logistic regression model.
... 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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Using Logistic Regression Model to Predict the Success of Bank Telemarketing
... 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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Logistic regression model training based on the approximate homomorphic encryption
... on logistic regression model, and biomed- ical data usually contain confidential information about individuals [3] which should be treated ...
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Determinants of Poverty on Household Characteristics in Zanzibar: A logistic Regression Model
... 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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Application of Binary Logistic Regression Model to Assess the Likelihood of Overweight
... 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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On goodness-of-fit of logistic regression model
... 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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LOGISTIC REGRESSION MODEL FOR PREDICTION OF BANKRUPTCY
... 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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An Application of Bootstrapping in Logistic Regression Model
... 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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Using Logistic Regression Model To Construct Insulator Spark Detection System
... 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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An Application on Multinomial Logistic Regression Model
... 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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Logistic Regression Model Training based on the Approximate Homomorphic Encryption
... 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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