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Maximum Likelihood Estimation Books

Elements of econometrics

Author: Dougherty

School: National Open University of Nigeria

Department: Administration, Social and Management science

Course Code: ECO356

Topics: Elements of econometrics, Simple regression analysis, econometrics, regression analysis, regression coefficients, hypothesis testing, Multiple regression analysis, Transformations of variables, Dummy variables, regression variables, Heteroscedasticity, Stochastic regressors, measurement errors, Simultaneous equations estimation, Binary choice, limited dependent variable models, maximum likelihood estimation, time series data, nonstationary time series, panel data, Regression analysis, linear algebra primer

Generalized Linear Models ,2nd Edition

Author: McCullagh, John Nelder

School: University of Ibadan

Department: Science and Technology

Course Code: STA351

Topics: Generalized Linear Models, dilution assay, probit analysis, logit models, log-linear models, inverse polynomical, survival data, model fittinf, residuals, pearson residual, Anscombe residual, deviance residual, error structure, systemic component, aliasing, estimation, tables, binary data, binomial distribution, over-dispersion, measurement scales, multinomial distribution, likelihood functions, log-linear models, multiple responses, conditional likelihoods, hypergeometric distributions, Gamma distribution, Quasi-likelihood functions, dependent observations, optimal estimating functions, optimality criteria, model checking, survival data, dispersion

Estimation of blood loss at delivery

Author: Grace Ezeoke

School: University of Ilorin

Department: Medical, Pharmaceutical and Health science

Course Code: OBSTETRICS AND GYNECOLOGY

Topics: Postpartum Hemorrhage

Introduction to econometrics ,3rd edition

Author: Christopher Dougherty

School: Modibbo Adama University of Technology

Department: Administration, Social and Management science

Course Code: MM306

Topics: Random variables, sampling theory, Covariance, variance, correlation, Simple regression analysis, regression coefficients, hypothesis testing, Multiple regression analysis, Transformations of variables, Dummy variables, Heteroscedasticity, Stochastic regressors, measurement errors, Binary choice, limited dependent models, maximum likelihood estimation, Autocorrelation

Statistical Inference 3

Author: OI Shittu

School: University of Ibadan

Department: Education

Course Code: SPE321

Topics: Statistical Inference, Point Estimation Techniques, Least Squares Method, Simple Linear Model, Least Squares Estimator, Maximum Likelihood, Cramer–Rao lower bound, Sufficiency, Fisher-Neyman Criterion, Test of Hypothesis

Introduction To Econometrics

Author: Samuel Olumuyiwa Olusanya

School: National Open University of Nigeria

Department: Administration, Social and Management science

Course Code: ECO355

Topics: Econometrics, Econometrics Model, Linear Regression, Regression Analysis, Ordinary Least Square Method Estimation, Classical Least Regression Method, Ordinary Least Square Estimators, Coefficient of Determination, Classical Normal Linear Regression Model, NORMAL LINEAR REGRESSION MODEL, SINGLE- EQUATION REGRESSION MODELS, ECONOMETRICS ANALYSIS, Method Of Maximum Likelihood, Confidence intervals, Regression Coefficients, Regression Analysis, Analysis of Variance, Normality

Introduction to Econometrics 2

Author: GA Adesina-Uthman, Okojie Daniel Esene

School: National Open University of Nigeria

Department: Administration, Social and Management science

Course Code: ECO356

Topics: Sampling Theory, Variance, Correlation, Econometrics, Random Variables, Sampling Theory, Covariance, Variance, Correlation, Regression Models, Hypothesis Testing, Dummy Variables.Simple Regression Analysis, Regression Coefficients, Multiple Regression Analysis, Multicollinearity, Transformations of Variables, regression variables, Heteroscedasticity/Heteroskedasticity, Autocorrelation, Error, Econometric Modelling, Stochastic Regression, measurement errors, Autocorrelation, Econometric Modelling, Time Series Data Models, Simultaneous Equation, Binary Choice, Maximum Likelihood Estimation

Mathematical Statistics with Applications,First Edition

Author: Kandethody Ramachandran, Chris Tsokos

School: Federal University of Technology, Minna

Department: Science and Technology

Course Code: STA117

Topics: Descriptive Statistics, Probability Theory, Sampling Distributions, point estimation, interval estimation, hypothesis testing, linear regression models, Analysis of Variance, Bayesian Estimation, Inference, nonparametric test, empirical method, set theory

Introduction to Linear Regression Analysis ,5th edition

Author: Elizabeth Peck, Geoffrey Vining, Douglas Montgomery

School: University of Ibadan

Department: Science and Technology

Course Code: STA351

Topics: Linear Regression Analysis, Regression, Model Building, Data Collection, Simple Linear Regression Model, Simple Linear Regression, Least-Squares Estimation, Hypothesis Testing, Interval Estimation, Multiple Regression Models, Multiple linear regression, Hypothesis Testing, Confidence Intervals, Standardized Regression Coefficients, Multicollinearity, Residual Analysis, model adequacy checking, Variance-Stabilizing Transformations, Generalized Least Squares, Weighted Least Squares, Regression Models, subsampling, Leverage, Measures of Influence, influence, Polynomial regression Models, Piecewise Polynomial Fitting, Nonparametric Regression, Kernel Regression, Locally Weighted Regression, Orthogonal Polynomials, Indicator Variables, Multicollinearity, Multicollinearity Diagnostics, Model-Building, regression models, Linear Regression Models, Nonlinear Regression Models, Nonlinear Least Squares, Logistic Regression Models, Poisson regression, Time Series Data, Detecting Autocorrelation, Durbin-Watson Test, Time Series Regression, Robust Regression, Inverse Estimation

Introduction to Linear Regression Analysis Solutions Manual for 5th edition

Author: Ann Ryan, Douglas Montgomery, Elizabeth Peck, Geoffrey Vining

School: University of Ibadan

Department: Science and Technology

Course Code: STA351

Topics: Linear Regression Analysis, Regression, Model Building, Data Collection, Simple Linear Regression Model, Simple Linear Regression, Least-Squares Estimation, Hypothesis Testing, Interval Estimation, Multiple Regression Models, Multiple linear regression, Hypothesis Testing, Confidence Intervals, Standardized Regression Coefficients, Multicollinearity, Residual Analysis, model adequacy checking, Variance-Stabilizing Transformations, Generalized Least Squares, Weighted Least Squares, Regression Models, subsampling, Leverage, Measures of Influence, influence, Polynomial regression Models, Piecewise Polynomial Fitting, Nonparametric Regression, Kernel Regression, Locally Weighted Regression, Orthogonal Polynomials, Indicator Variables, Multicollinearity, Multicollinearity Diagnostics, Model-Building, regression models, Linear Regression Models, Nonlinear Regression Models, Nonlinear Least Squares, Logistic Regression Models, Poisson regression, Time Series Data, Detecting Autocorrelation, Durbin-Watson Test, Time Series Regression, Robust Regression, Inverse Estimation

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