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Semiparametric and Nonparametric Methods in Econometrics

Standard methods for estimating empirical models in economics and many other fields rely on strong assumptions about functional forms and;

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Probability and Statistics

basics of sampling distributions, estimation and hypothesis testing. As a companion for classes for engineers and scientists, the book also;

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Statistical and Mathematical Sciences and Their Applications

experiments, balanced sampling plans, estimation procedures for reliability function, generalized Horvitz-Thompson estimator, Searle's type;

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Probability and Statistics in Experimental Physics

, robustness estimates, and likelihood ratios; interpolating functions and unfolding problems; fitting data with constraints; robust estimation methods.;

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Statistical Simulation

Although power method polynomials based on the standard normal distributions have been used in many different contexts for the past 30;

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Statistical Simulation

Although power method polynomials based on the standard normal distributions have been used in many different contexts for the past 30;

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COSMIC Function Points

has become the major estimation technique based on international standards for building software-intensive systems. COSMIC Function Points;

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Cosmic Function Points

has become the major estimation technique based on international standards for building software-intensive systems. COSMIC Function Points;

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Probability Concepts in Engineering Planning and Design

Randomness 1.2.2. Uncertainty Associated with Imperfect Modeling and Estimation 1.3. Design and Decision-Making Under Uncertainty 1.3.1. Planning and;

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A study of Rayleigh Fading Channel Models

been studied, simulated and compared based on the Rayleigh fading process properties. Various communication systems have been simulated using;

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Ultrasonic Methods for Measurement of Small Motion and Deformation of Biological Tissues for Assessment of Viscoelasticity

center frequency variation on the estimation of motion and deformation, an error correcting function, which does not require the assumption that;

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Power System State Estimation

overview of power system operation and the role of state estimation in overall energy management. It uses an abundance of examples, models, tables;

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Introduction To Bayesian Econometrics

of probability to ensure coherency. It defines the likelihood function, prior distributions and posterior distributions. It explains how posterior;

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Statistical Estimation for Truncated Exponential Families

This book presents new findings on nonregular statistical estimation. Unlike other books on this topic, its major emphasis is on helping;

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Mathematical Statistics

uniquely based on the likelihood function This book addresses mathematical statistics for upper-undergraduates and first year graduate students;

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Introduction to Robust Estimation and Hypothesis Testing

Introduction to Robust Estimating and Hypothesis Testing, 4th Editon,is a 'how-to' on the application of robust methods using available;

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Bayesian Deconvolution of Sparse Processes

-Gaussian model. Methods based on the expectation-maximization algorithm are investigated for both models, and several statistical inference and;

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Classical and Modern Direction-of-Arrival Estimation

Classical and Modern Direction of Arrival Estimation contains both theory and practice of direction finding by the leading researchers;

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Introduction to Bayesian Econometrics

rules of probability to ensure coherency. It defines the likelihood function, prior distributions and posterior distributions. It explains how;

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An Introduction to Generalized Linear Models

focusing on methods for analyzing particular kinds of data. It covers normal, Poisson, and binomial distributions; linear regression models;

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Shrinkage Estimation

statistical properties. The book focuses primarily on point and loss estimation of the mean vector of multivariate normal and spherically symmetric;

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Handbook of Exponential and Related Distributions for Engineers and Scientists

chapter deals with system reliability for series and parallel systems. Presenting methods based on statistical simulations and numerical;

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Finite Mixture of Skewed Distributions

mixtures of skew normal distributions (SMSN). For this purpose, the authors consider maximum likelihood estimation for univariate and multivariate;

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Applied Statistical Science III

, Exponential Families and Recursive Estimation; Some Quick Estimators Based on Sample Maxima; Inferences of Power Function Distribution Based on;

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Fundamental Statistical Inference

include an intuitive presentation of the (single and double) bootstrap for confidence interval calculations, shrinkage estimation, tail (maximal;

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Statistical Methods For Speech Recogniti

, maximum entropy probability estimation, parameter and data clustering, and smoothing of probability distributions. The author's goal is to present;

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