Read-alikes and related books

Books like Introduction to Variance Estimation

If you loved Introduction to Variance Estimation by Kirk Wolter, this shelf of 24 books shares the same pull — rooted in Stochastic Processes, Probability & Statistics, and Mathematics.

Stochastic Processes Probability & Statistics Mathematics

Top related books to Introduction to Variance Estimation

Read-alikes chosen for how well they continue the mood, themes, and voice of Introduction to Variance Estimation.

Empirical Studies on Volatility in International Stock Markets — Eugenie M.J.H. Hol

Empirical Studies on Volatility in International Stock Markets

Eugenie M.J.H. Hol

Themes: Stochastic Processes • Probability & Statistics • Mathematics

A Computational Approach to Statistical Learning — Taylor Arnold

A Computational Approach to Statistical Learning

Themes: Stochastic Processes • Probability & Statistics • Mathematics

ЧИСЛЕННЫЕ МЕТОДЫ РАСЧЕТА ЯДЕРНЫХ РЕАКТОРОВ / Chislennye Metody Rascheta Yadernykh Reaktorov / Numerical Methods for Nuclear Reactor Calculations — Gurji I. Marchuk

ЧИСЛЕННЫЕ МЕТОДЫ РАСЧЕТА ЯДЕРНЫХ РЕАКТОРОВ / Chislennye Metody Rascheta Yadernykh Reaktorov / Numerical Methods for Nuclear Reactor Calculations

Gurji I. Marchuk

Themes: Stochastic Processes • Probability & Statistics • Mathematics

Introduction to Bayesian Statistics — William M. Bolstad

Introduction to Bayesian Statistics

William M. Bolstad

Themes: Stochastic Processes • Probability & Statistics • Mathematics

Handbook of Exchange Rates — Jessica James

Handbook of Exchange Rates

Themes: Stochastic Processes • Probability & Statistics • Mathematics

The Structural Theory of Probability New Ideas from Computer Science on the Ancient Problem of Probability Interpretation — Paolo Rocchi

The Structural Theory of Probability New Ideas from Computer Science on the Ancient Problem of Probability Interpretation

Themes: Stochastic Processes • Probability & Statistics • Mathematics

Nonparametric Curve Estimation Methods, Theory, and Applications — Sam Efromovich

Nonparametric Curve Estimation Methods, Theory, and Applications

Themes: Stochastic Processes • Probability & Statistics • Mathematics

Introduction to Stochastic Processes with R — Robert P. Dobrow

Introduction to Stochastic Processes with R

Robert P. Dobrow

Themes: Stochastic Processes • Probability & Statistics • Mathematics

Lévy-Type Processes Under Uncertainty and Related Nonlocal Equations — Julian Hollender

Lévy-Type Processes Under Uncertainty and Related Nonlocal Equations

Julian Hollender

Themes: Stochastic Processes • Probability & Statistics • Mathematics

The Statistical Analysis of Failure Time Data — John D. Kalbfleisch

The Statistical Analysis of Failure Time Data

John D. Kalbfleisch

Themes: Stochastic Processes • Probability & Statistics • Mathematics

Assessing and Improving Prediction and Classification Theory and Algorithms in C++ — Timothy Masters

Assessing and Improving Prediction and Classification Theory and Algorithms in C++

Timothy Masters

Themes: Stochastic Processes • Probability & Statistics • Mathematics

High Performance Discovery In Time Series Techniques and Case Studies — Dennis Elliott Shasha

High Performance Discovery In Time Series Techniques and Case Studies

Dennis Elliott Shasha

Themes: Stochastic Processes • Probability & Statistics • Mathematics

Information and Complexity in Statistical Modeling — Jorma Rissanen

Information and Complexity in Statistical Modeling

Themes: Stochastic Processes • Probability & Statistics • Mathematics

Seminar on Stochastic Processes, 1983 — Cinlar

Seminar on Stochastic Processes, 1983

Themes: Stochastic Processes • Probability & Statistics • Mathematics

Topics from Australian Conferences on Teaching Statistics OZCOTS 2008-2012 — Helen MacGillivray

Topics from Australian Conferences on Teaching Statistics OZCOTS 2008-2012

Helen MacGillivray

Themes: Stochastic Processes • Probability & Statistics • Mathematics

Optimal Control Theory, Algorithms, and Applications — William W. Hager

Optimal Control Theory, Algorithms, and Applications

William W. Hager

Themes: Stochastic Processes • Probability & Statistics • Mathematics

Growth Curve Models and Statistical Diagnostics — Jian-Xin Pan

Growth Curve Models and Statistical Diagnostics

Themes: Stochastic Processes • Probability & Statistics • Mathematics

Data Mining and Statistics for Decision Making — Stéphane Tufféry

Data Mining and Statistics for Decision Making

Stéphane Tufféry

Themes: Stochastic Processes • Probability & Statistics • Mathematics

Genetic Programming Theory and Practice III — Tina Yu

Genetic Programming Theory and Practice III

Themes: Stochastic Processes • Probability & Statistics • Mathematics

Distributions With Given Marginals and Statistical Modelling — Carles M. Cuadras

Distributions With Given Marginals and Statistical Modelling

Carles M. Cuadras

Themes: Stochastic Processes • Probability & Statistics • Mathematics

Time Series Applications to Finance with R and S-Plus — Ngai Hang Chan

Time Series Applications to Finance with R and S-Plus

Themes: Stochastic Processes • Probability & Statistics • Mathematics

activity-based statistics — Richard L. Scheaffer

activity-based statistics — Richard L. Scheaffer

Richard L Scheaffer

Themes: Stochastic Processes • Probability & Statistics • Mathematics

A Step-by-Step Approach to Using SAS for Univariate and Multivariate Statistics — Norm O’Rourke

A Step-by-Step Approach to Using SAS for Univariate and Multivariate Statistics — Norm O’Rourke

Themes: Stochastic Processes • Probability & Statistics • Mathematics

Asymptotic Theory of Statistics and Probability — Anirban DasGupta

Asymptotic Theory of Statistics and Probability

Anirban DasGupta

Themes: Stochastic Processes • Probability & Statistics • Mathematics

This list brings together 24 books that share meaningful common ground with Introduction to Variance Estimation by Kirk Wolter. Connected by Stochastic Processes, Probability & Statistics, Mathematics. Authors featured include Eugenie M.J.H. Hol, Taylor Arnold, Gurji I. Marchuk, William M. Bolstad, and others. Each pick was selected for thematic and literary overlap — not just genre similarity.

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