regression model

The regression model is then used to predict the result of an unknown dependent variable, given the values of the independent variables.

We establish the combined regression-time-series model for Chinese inflation and compare its forecast results to that of regression model.

It's actually quite easy to put our data through the regression model using the WEKA API, far easier than actually loading the data.

Settlement of earth-rockfill dam is mainly influenced by aging deformation and regression model is usually adopted for settlement analysis.

The principal component model and the regression model between the total dissolved solids and ions content were established in this paper.

Finally, since the vector regression model more precise simulation of the ship of the timecharte rental level of the trend.

Reference control points(RCPs) used to establish the regression model in registration are commonly assumed "perfect" .

Then, this paper uses the logit regression model to test the relation between the top management turnovers and performance.

Linear regression model is useful to evaluate the adaptation of a quantitative character to the change of environments.

The conclusion can be drawn that the optimal heat transfer performance of PHP can be achieved by solving for extremum of regression model.

Thirdly, this paper analyzes the influence of each factor on China's education service trade through multivariate regression model.

Therefore, the Hurdle model can be considered the combination of binary regression model and the zero-truncated count model.

Then, correlation index and regression model are used to forecast population scale, urban quantity and urbanization in Jiangsu province.

The Six Sigma Black Belt will be able to identify patterns in residuals from an improper regression model and to apply the correct remedy.

Owing to the conventional linear regression model is sensitive to abnormal data, therefore the regression equation is not stable en ough .

Set representation, Fuzzy random variables, Fuzzy regression model, Fuzzy expected value, Fuzzy distribution function, Fuzzy unbiased.

Simple linear regression model is applied to compare the difference in SGA usage pattern between public and private hospitals.

Meanwhile, a linear regression model and a BP neural network model for predicting the springback quantity were set up.

Examples show that: semi-parametric regression model fitting results is better applied to load forecasting.

Running a classification, clustering, or Nearest Neighbor isn't quite as easy as a regression model, but they aren't much harder.

A regression model of urban rail transit system is established and used to predict the power consumption of Shanghai Metro Line 5.

Real exchange rate; Mechanical&Electrical Products; Cointegration test; Vector auto-regression model.

It has also carried partial least-squares regression model to the precision analysis.

Secondly, indicators of spatial autocorrelation and the spatial regression model are introduced to explore and examine spatial effects.

Regression model obtained after the model test of significance, including the model test of significance, test of significance coefficient.

Finally, in order to understand this issue more deeply, we also build churn prediction model with Logistic regression model.

Trip generation takes the distance into account, adds accessibility variable into the regression model.

To establish COX regression model analysis the independent factors on the survival prognosis of patients with cervical cancer.

Under these basic financial indicators, we using logistic regression to generate regression model, and verified.

A regression model is formulated then to illustrate how metacognitive strategy use is predicable of language proficiency.

This is all the same as we saw in the regression model.

After data preprocessing, a regression model between calorific and ash content was founded by polynomial regression.

Means filling; Imputation at random; EM algorithm; Regression model; Multiple imputation.

This regression model is easy to use and can be used for myriad data sets.

BP neutral network model improved the accuracy of regression model in predicting soil detachment rate in every type of road.

The comparison demonstrates that the model is superior to linear regression model in precision.

Ultimately determine the optimal linear regression model, and apply the simple model predictions.

Objective To sump up and extend COX regression model with categorical variables.

Establish regression model, substituting the x value into the model, the calculated y values.

So, a multi-linear regression model for estimation pharmacokinetic parameters of metformin by using LSS method is feasible.

The ordinary Least Squares Estimate (LSE) in linear regression model is not robust for many cases.

A high precise regression model of rubber formulation was built with the uniform design and GMDH (group method of data handling) method.

It puts the regression model right there in the output, as shown in Listing 2.

To overcome this drawback, the orthogonal least square regression model is introduced.

Reasons why we want a Regression Model: 1. Descriptive - form the strength of the association between outcome and factors of interest, 2.

Also, the regression model of soil erosion and runoff velocity is developed by statistics method in this paper.

Everyone has probably used or seen a regression model before, maybe even mentally creating a regression model.

Based on the economic analysis of the results of Regression model, this part gives the corresponding policy recommendations.

Derived from regression model fitting in good condition and meet the design requirements.

Through this empirical analysis, it establishes the multiple factor regression model to provide useful suggestions for them.

Then, the polynomial regression model becomes a reasonable choice.

Finally in the feature space using least-square method to extract the linear regression model, and the model test.

Then had a regression analysis of force data using the EXCEL software to establish the 3A21 regression model of cutting force.

The regression model for contaminated data is a useful model in biostatistics.

A method of extracting features based on car shape contour was provided and regression model was applied to analysis in the paper.

Finally, we used the DEA model, regression model to verify the theoretical analysis.

Accordingly, a regression model with virtual independent variables is built to forecast the demand of human resourses.

As for a large-scaled linear regression model, a fast algorithm to pick out outliers is presented based on the one-by-one method.

Objective To discuss random effects Poisson regression model forrepeated count data in clinical trial.

Date were drawn from the '2001 Taiwan Election and Democratization Survey' and analyzed in a 2-level logistic regression model.

Using entity fixed effects regression model of industry-level panel data.

The regression model has guiding significance to the study on ternary dissymmetric organic phosphate insecticide.

The fifth chapter seeks potential approach to improve the liquidity of Real Estate Company based on the regression model.

Using the same regression model, this paper compares the influences of different factors.

A logistic regression model must contain a key column, one or more input columns, and one or more predictable columns.

Based on a descriptive analysis, this paper adopts the 2-Logistic regression model for regression statistical analysis.

After that, a multiple linear regression model was built in accordance with theoretical analysis.

This paper proposes a short term load forecasting (STLF) method by using clustering based support vector regression model.

As a result, the regression model can effectively approximate multi-scale signals.

The problem of testing the fit of linear regression model under the depth-weighted LSE were also discussed.

He has used a tool of economic analysis, called a vector auto-regression model.

A linear multi-regression model as thus made in the end, the authors flied to predict the current and quantity of the farmland change.

Now that the data file has been created, it's time to create our regression model.

So go ahead and create the regression model.

In order to find the factors affecting IPO pricing, we try to build the multiple linear regression model.

So this regression model is telling us that granite in your kitchen doesn't affect the house's value.

Using the open-end stock funds data from 2001 to 2008, it introduces dummy variables in the fixed-effect regression model.

Let's continue this example of a house price-based regression model, and create some real data to examine.

Finally, the city which is the most potential for economy hotel chain growth in China is forecasted based on the regression model.

And we forecast the vehicle population from 2007 to 2017 by use of multi-linear regression model.

A logistic regression model was then used to study factors predicting severity of foot injury.

So, if you've ever bought a house or sold a house, you've likely created a regression model to price the house.

Secondly, Fitting regression model has been used to predict the scale of urban and rural built-land in the year of 2010 and 2020;

Regression model on the total value of agricultural output against the cultivated area of the crops in Baotou

The relative efficiencies of a class of linear estimator with respect to generalized least square estimator in linear regression model

Influence Analysis on Best Linear Unbiased Estimate in the General Linear Regression Model

Influence Analysis of Ridge Estimator in the General Linear Regression Model

The Application of Disturbing Linear Regression Model in the Short-term Anticipation on the Products of a Manufacturer

Strong Convergence Rates of the Estimators for a Class of Semiparametric Regression Model

Strong Consistency for Estimators of a Class Semi-Parametric Reliability Regression Model

Strong Consistency for Estimators of a Class Semi-Parametric Reliability Regression Model

secondly, predict the immigration crime development tendency in Bincheng district by setting up a regression model;

Strong Consistency of Estimators of a Semiparametric Regression Model under Fixed Design

Estimated Theory of Semiparametric Regression Model With Heteroscedasticity

Nonuniform Convergence Rates of the Distributions of Error Variance Estimates in Semiparametric Regression Model

Consistent Estimator of the Nuisance Parameter in a Semiparametric Regression Model

A study on linear regression model with fuzzy weight and its application to S-N curve in its regression analysis

The Asymptotic Properties of a Semiparametric Regression Model Under Fixed Design

Strong Consistent Estimation in Semiparametric Regression Model for the Longitudinal Contaminated Data

Logistic regression model for the relationship between serum homocysteine and coronary atherosclerosis

Annual Precipitation Prediction for Panyu with a Successive Regression Model

residuals in the classical regression model exhibited regional differentiation that reveals spatial heterogeneity;

Regression Parameters Estimation of Random-Fuzzy Linear Regression Model and its Application

Large sample properties of the estimation of the error distribution for a semiparamentric regression model

Testing Heteroscedasticity by Wavelets in a Nonparametric Regression Model with Random Design

Homogeneous linear minimax estimation for regression coefficients in multivariate regression model

Constructing a Cox Proportional Hazard Regression Model of Prognosis Factors of Acute Myocardial Infarction by Retrospective Cohort Study

Forecasting Research on Listed Companies Acquired by State-Owned Enterprises and Private Enterprises Using Logistic Regression Model

established multiple regression model and BP neural network model of the groundwater level and predict the groundwater level;

Partial Least Square Regression Model of Ecological Footprint and Its Influencing Factors

Determination of ethanol content in distilled spirits using short-wave near infrared spectroscopy with partial least square regression model

Cumulative method in semiparametric regression model--nonparametric estimator base on wavelet smoothing

Dynamic Regression Model, Dynamic Regression, Dynamic regression model, Dynamic regression

Deducing and Estimating Nonparametric Signal in Semiparametric Regression Model--Method of Cubic Splines Interpolation

Application of Project Pursuit Auto-regression Model and Strain Accumulating and Releasing Model to Earthquake Trend Prediction in Xinjiang

An Adaptive Regression Model of Population Prediction and Its Experiential Studying

Relative efficiencies of parameter estimator in a class of seemingly unrelated regression model

MultiVarRegr A Network Software of Multivariable Regression Model Used in Statistical Analysis of Information

Establishment and evaluation of bone mineral density reference databases for multiple skeletal regions in women by cubic regression model

High-tech Small and Medium Enterprises; Financing Efficiency; Effect Factors; DEA Method; Multiple Linear Regression Model;

Demonstrational Research on Investors'Motivations on Dualistic Logistic Regression Model

Predicting Polymer-Flooding Development Indexes Using Regression Model Technology

Community Supermarket; Location Factors; Micro-Location; Regression Model;

Optimal Multiple Regression Model with Constraints and its Application

Estimation for a Class of Semiparametric Regression Model with Censored Data

Comparison of nonlinearity disposing ability between Cox proportional hazards regression model and BP Neural Network

Distribution Approximation in Censored Regression Model by Randomly Weighting Bootstrap

Near Neighbour Estimate in Semiparametric Regression Model: The Martingale Difference Error Sequence Case

Weighted Regression Model and Its Application with Membership Function as Weight

Comparison of the Efficiency of Least Square Estimator in Regression Model for Longitudinal Data by Simulation

Strong Consistency Estimation in Semiparametric Regression Model for Contaminated Data

Influence Analysis in Multivariate Regression Model with Covariance Matrix Disturbance

Mean Consistency for a Semiparametric Regression Model

The construction and amendment research of the regression model of Fetus heteroplasia screening

Small-sample properties for generalized ridge estimator of regression coefficients in linear regression model

Then using statistics method, establishing the regression model of straight line and analyzing join level for regression model;

Parameter Estimation of a Regression Model Under Censored Data

Studies on grey relation degree analysis and multivariate regression model optimization of biomass pyrolysis

Influence Analysis in Multivariate Regression Model with Covariate Matrix Disturbance

Prediction Test with Multivariate Mixed Threshold Regression Model for Rainy Season Precipitation

Asymptotic Properties of Semiparametric Regression Model for Longitudinal Data

Variance Estimation of Error in a Semiparametric Regression Model with Censored Data

COX regression model with categorical variables and its application

The building of mathematical regression model of prototype of female large bust and waist figure

The Conditional Ridge-type Estimation of Regression Coefficient in Restricted Linear Regression Model

Strong Consistency of Estimators in Semiparametric Regression Model for Longitudinal Data

Random Weighted Approximation in Semiparametric Regression Model Under Fixed Design

Semiparametric Regression Model With Natural Spline and Systematic Error Estimation

The Determination of Orders of the Polynomial Regression Model in Multi-beam Phase Difference Series

Local Linear Least Squares Estimation in Semiparametric Regression Model for Longitudinal Data

Parameter Estimations and Interval Estimation in Linear Regression Model for Contaminated Data

Dynamic - regression model of per capital annual expenditure on consumption in Shandong countryside

Consistency of Estimators in Semiparametric Regression Model for Longitudinal Data

Combination Regression Model With Scattered Coefficient of Non-Stationary Sequence

Study on Land Degradation Trend by Applying Logistic Multivariate Regression Model in Northwest Region of Beijing

Linear Regression Model with Fuzzy Weight of Fatigue Curve and Its Applications

Experiential Curve Nonlinear Regression Model for Sediment Prediction of Soft Soil Foundation

The Performance Comparison of Several Estimate for Linear Weighted Regression Model Presented

Project pursuit regression model for diffusion coefficient of suspended particles in liquid-solid two-phase flow

The Asymptotic Properties of Wavelet Estimationin Semiparametric Regression Model Under Random Censorship

Estimating Covariance Functions for Daily Milk Yields of Holstein Dairy Cows in Hunan Using a Random Regression Model

Cubic regression model between P. euphratica foliage cover and groundwater level and Quadratic regression model with groundwater salinity;

Clustering Based on Support Vector Regression Model and Its Application in Power System Transient Stability Prediction

Likelihood Estimation of Regression Model Under Transformation

The Geographically Weighted Regression Model and Its Fit Methods

Edgeworth expansion of random weighting estimation in semi-parametric regression model

Two-step Procedure and Numerical Simulations for Semiparametric Spatially Varying-Coefficient Regression Model

Analysis and Improvement to Linearization Nonlinear Regression Model

New Solution of a Kind of Pure Nonlinear Regression Model and Its Application

Destructiveness for the Results of Small Disturbance of Non-initial Data in Linear Regression Model

Bayesian Predictive Analysis of the Multiple Linear Regression Model

Linear Regression Model Ridge Trace Selection Procedure and Application Research

Nonparametric Regression Model with Natural Spline and Simulation Analysis

The Robustness of Linear Regression Model in Rice Leaf Chlorophyll Concentration Prediction

Local Polynomial Smoothing to Semiparametric Regression Model

Applying Varying- Coefficient Regression Model in Econometric

Linear Regression Model for Composite Stock Index of Shanghai Stock Exchange Centre (Daily Closing Price)

Estimation Method of Semiparametric Regression Model with Contaminated and Censored Data

Strong Consistency of Estimators for Semiparametric Regression Model Under NA Samples

Support Vector Regression Model with Wavelet Reproducing Kernel for Function Learning

Convergence rates of M-estimates in a semiparametric regression model

Studies on photosynthetic simulation in greenhouse eggplant by regression model

A Regression Model Based on Double Parameters Poisson Distribution and Its Applications to Risk Classification

Multiple Linear Regression Model Analysis of Pricing in a Maturity Market

Study of Selection of Linear Regression Model According to the Parameter Estimation

Regression Model of Characteristics of Effective Panicle Formation of Tiller, Yield Traits and Yield in Rice

Prediction of Lateral Acceleration of Locomotives and Rolling Stock on the Basis of Linear Regression Model

Stationary Tests of Geographically Weighted Regression Model

Algorithm for Mixed Geographically Weighted Regression Model

A Note on Estimation Theory of Semiparametric Regression Model with Censored Data

Molecular Marker Regression Model and Dominant Molecular Marker Material

The partial least square regression model for predicting copper biological toxicity

Mixed Regression Model Has Random Restriction and Random Restricted Ridge-type Estimator

Application of Partial Least Squares Regression Model to the Related Analysis of Hydrology

Optimal Choice of a Practical Regression Model

Regression Model Analysis of the Relationship among Catches of Main Fishes in Lake Taihu

Analysis of Risk Factors of Recurrent Inguinal Hernia by Cox Proportional Hazard Regression Model

Used of Covariance Adjustment Estimator In the Seemingly Unrelated Regression Model

Study on Quantitative Analysis with Near-infrared Spectra Using Latent Root Regression Model

Nonparametric Multivariate Regression Model of Urban Daily Water Demand

Bayesian predictive analysis of multiple linear regression model system

Strong Consistency Estimation in Regression Model for Contaminated Data

Influence analysis in weighted regression model with perturbation

Applications of Weighted Regression Model and Weighted GM in Slope Deformation Forecast

Non-parametric Regression Model Based Short-term Prediction for Expressway Travel Speed

Robust Estimation in Semiparametric Regression Model

The Regression Model Used in Optimizing Operation of Pump Sets

Application of linear regression model in Economic Activities Analysis

Constrained Quasi Likelihood in Nonlinear Regression Model

Semiparametric regression model with linear process errors

Application of multi-variate auto-regression model to forecast water demand of well irrigated paddy

Method of Randomizing the Restrictive Conditions of Nonlinear Regression Model

Dam Safety Monitoring Threshold Regression Model and Application

Consistency Estimation in Regression Model for Contaminated Data

The Optimization of the Mathematical Regression Model

Study on joint application of grey relevancy analysis and multiple linear regression model

Application of progressive regression model in monitoring of uplift on dam foundation

Flood Season Rainfall Forecast in Zhaoqing using a Successive Regression Model

Analysis of the Present State of Service Industry in Shandong Province Based on Linear Regression Model

Nonparametric regression model of chinese inflation

Bayes Interval Estimation of Linear Regression Model Parameters

Nonlinear Regression Model for Increment of Scientific Document

TransforMations and Influential Cases in Regression Model

The Integration Regression Model for Economic Forecasting

Further Study on Methods in Handling Multi-variable Collinearity in Cox Regression Model

Dominance Analysis: Method for Determining Relative Importance of Predictors in Multiple Regression Model

Robust universal least squares estimation in linear regression model

Application of Analytic Hierarchy Process in Linear Regression Model

Using Local Linear Technique to the Semiparametric TBS Regression Model

Application of Regression Model to Predict Seasonal Trend of Cancer Patient Numbers

An interval estimator of error variance in nonparametric regression model

Semi-theoretical augmented mixed regression model of water distribution network

An Application of Multi-Variated Linear Regression Model to the Trend of Water Resource Stress in Changchun City

Multi-regression Model's Application in the Seepage Stability Forecast of Dam Foundation

Comparison between BP neural network model and statistical regression model of dam

The Establishment of Regression Model for Rock Compressive Strength

A Support Vector Regression Model for the Predicting of Infant Mortality

Study on the Regression Model of Ballast Impedance of Track Circuit with Concrete Sleepers

Water surface profile regression model of Mudanjiang River in Mudanjiang

The Research of Application of Semi-Parameter Regression Model to Price Index of Housing for Sale

BC Estimation of Parameter in Multivariate Linear Regression Model

Edgeworth Expansion of L-Estimators in Semi-parametric Regression Model

Adaptive Inverse Control Based on an Incremental Linear Regression Model in One Unknown

Application of Multivariate Linear Regression Model Based on Gray Interaction Analysis in Medium and Long Term Hydrologic Forecast

Short Term Load Forecasting Using Chaos Phase Space Mode Linear Regression Model

Application and Improvement of Auto-regression Model in Prediction of Well Depth

The Multiple Regression Model of Librarians'Job Satisfaction

Net-Point Observed Partial Linear Regression Model with Errors in Variables

Local influence of linear regression model with structural change

Estimation of Semi- Parameter Regression Model with Censored Data