| Call Number (LC) | Title | Results |
|---|---|---|
| QA276.8 .T79 2006 | Semiparametric theory and missing data / | 1 |
| QA276.8 .U53 2019 | Uncertainty. | 1 |
| QA276.8 .V32 1988 | Statistical estimation in large parameter spaces / | 1 |
| QA276.8 .V3613 2006eb | Estimation of dependences based on empirical data | 1 |
| QA276.8 .V6413 1993 | Unbiased estimators and their applications / | 1 |
| QA276.8 .W37 1970 | Parametric estimation / | 1 |
| QA276.8 .W44 1998 | Entropy methods in statistical estimation / | 1 |
| QA276.8 .W45 2008eb | Guesstimation : solving the world's problems on the back of a cocktail napkin / | 1 |
| QA276.8 .W45 2012eb | Guesstimation 2.0 : Solving Today's Problems on the Back of a Napkin / | 2 |
| QA276.8 .W54 1997 | Nonparametric estimation for a windowed line-segment process / | 1 |
| QA276.8 .W54 2019 |
Learn about density estimation in Stata with the Cardiac Catheterization Diagnostic Dataset (2018) / Learn to use stratified data in Stata with data from the IRCBP Public Services Baseline Survey (2005) / Learn to use maximum likelihood parameter estimation in Stata with the Cardiac Catheterization Diagnostic Dataset (2018) / |
3 |
| QA276.8 .W55 1997 | Introduction to robust estimation and hypothesis testing / | 1 |
| QA276.8 .W55 2005 | Introduction to robust estimation and hypothesis testing / | 1 |
| QA276.8 .W55 2012 | Introduction to robust estimation and hypothesis testing | 1 |
| QA276.8 .W558 2012 | Introduction to Robust Estimation and Hypothesis Testing. | 2 |
| QA276.8 .W56 2013eb | Measurement uncertainty and probability / | 2 |
| QA276.8 .Y68 1984 | Recursive estimation and time-series analysis : an introduction / | 1 |
| QA276.8 .Y68 2011 | Recursive estimation and time-series analysis an introduction for the student and practitioner / | 1 |
| QA276.8 .Z34 2021 | High-dimensional covariance matrix estimation : an introduction to random matrix theory / | 1 |
| QA276.8 .Z53 2011 |
Comparing groups randomization and bootstrap methods using R / Comparing groups : randomization and bootstrap methods using R / |
2 |
