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regression model

The Regression Model for the Statistical Analysis of Albanian Economy

The Regression Model for the Statistical Analysis of Albanian Economy

... multiple regression analysis (MRA) will be used to demonstrate the economic trend of transitory economy of ...multiple regression model (MRM) in a case ...

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Outlier detection in a circular regression model

Outlier detection in a circular regression model

... Circular regression attempts to model the relationship between a circular dependent and a set of circular independent ...circular regression model of two circular variables u and v mimicking ...

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On goodness-of-fit of logistic regression model

On goodness-of-fit of logistic regression model

... model. The space shuttle Challenger accident occurred on January 28, 1986. An O- ring that was used to seal a joint of the booster rockets experienced thermal distress. The Rogers Commission appointed by President ...

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Efficient Estimation of an Additive Quantile Regression Model

Efficient Estimation of an Additive Quantile Regression Model

... In this paper two kernel-based nonparametric estimators are proposed for estimating the components of an additive quantile regression model. The first estimator is a computationally convenient approach ...

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Fuzzy Regression Model and Its Application: A Review

Fuzzy Regression Model and Its Application: A Review

... linear regression model with crisp input and fuzzy output described by Tanaka was considered ...liner regression model with non fuzzy input and fuzzy output data type to handle the outlier in ...

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An Application of Bootstrapping in Logistic Regression Model

An Application of Bootstrapping in Logistic Regression Model

... 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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A Logistic Regression Model of Determiner Omission in PPs

A Logistic Regression Model of Determiner Omission in PPs

... logistic regression model of deter- miner omission in German based on data obtained by applying annotation mining to a large, automatically and manually annotated ...

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Choosing Appropriate Regression Model in the Presence of Multicolinearity

Choosing Appropriate Regression Model in the Presence of Multicolinearity

... in regression analysis, given the se- rious threat it poses on the validity or the predicting strength of the regression ...in regression, especially multiple regressions when there is a high level ...

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Statistical methodology for regression model with measurement error

Statistical methodology for regression model with measurement error

... One of the most widely known techniques for slope estimator of the simple linear regression model with measurement error is the method of higher-order moments. Many statistical books have referred to this ...

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LOGISTIC REGRESSION MODEL FOR PREDICTION OF BANKRUPTCY

LOGISTIC REGRESSION MODEL FOR PREDICTION OF BANKRUPTCY

... logistic regression was carried out to identify the factors which are jointly responsible for the successive level of the ...logistic regression was carried out using forward inclusion and backward ...

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A regression model for vessel turnaround time

A regression model for vessel turnaround time

... a regression model that relates these variables, ...such model include giving port operators opportunity to determine optimum crane allocation to achieve the desired turnaround time given the ...

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Regression model analysis for vessel service time

Regression model analysis for vessel service time

... This research seeks to identify the problems related to vessel turnaround time. So far, there have been researches in this area where the objective was to minimise the time vessels spend at berth (Preston et al., 2001). ...

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Nonparametric and semiparametric regression model selection

Nonparametric and semiparametric regression model selection

... based model selection procedure for the choice of both the parametric and nonparametric time series components in semiparametric time series regression, and then establish some asymp- totic properties of ...

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A generalized panel data switching regression model

A generalized panel data switching regression model

... data model of polychotomous switching which also allows for the dependence between unobserved effects and covariates in the ...The model we consider can be thought of as a generalization of a standard ...

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An Application on Multinomial Logistic Regression Model

An Application on Multinomial Logistic Regression Model

... 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 categories, whether nominal ...

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RESTRICTIONS IN REGRESSION MODEL

RESTRICTIONS IN REGRESSION MODEL

... When no equal sign appears, the linear combination is set equal to zero. Each variable name mentioned must be a variable in the MODEL statement to which the RESTRICT statement refers. The keyword INTERCEPT can ...

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Modelling and Forecasting of Residential Electricity Consumption in Nigeria Using Multiple Linear Regression Model and Quadratic Regression Model with Interactions

Modelling and Forecasting of Residential Electricity Consumption in Nigeria Using Multiple Linear Regression Model and Quadratic Regression Model with Interactions

... models. Model 2 (the Quadratic Regression with interaction) gave the highest value of coefficient of determination (r 2) compared with model 1 (the Multiple Linear Regression ...Also, ...

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On Inference of the Linear Regression Model with Groupwise Heteroscedasticity

On Inference of the Linear Regression Model with Groupwise Heteroscedasticity

... It is common practice to use the HCCMEs to get the consistent estimates of variances of the OLS estimates for heteroscedastic linear regression models. In many practical situations, averages of the dependent and ...

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Bayesian Model Averaging in the Instrumental Variable Regression Model

Bayesian Model Averaging in the Instrumental Variable Regression Model

... 1983, Sargan, 1958). Given the large number of possible models, the re- peated application of diagnostic tests will result in similar distorted size and power properties as arise in the regression model ...

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Air Quality Prediction Through Regression Model

Air Quality Prediction Through Regression Model

... Logistic regression is used to detect whether a data sample was either polluted or not ...linear regression and artificial neural network (ANN) Protocol for prediction of the pollution of the next ...linear ...

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