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An Introduction to Bootstrap Methods with Applications to R
An Introduction to Bootstrap Methods with Applications to R

Pi and the Fibonacci Numbers
Pi and the Fibonacci Numbers

Testing Conditional Factor Models
Testing Conditional Factor Models

... but also examine one-sided and uniform kernels that have been used in the literature by Andersen et al. (2006) and Lewellen and Nagel (2006), among others. In common with other nonparametric estimation methods, as long as the kernel is symmetric, the most important choice is not so much the shape o ...
Méthodes non-paramétriques pour la prévision d - ENAC
Méthodes non-paramétriques pour la prévision d - ENAC

Multiple Fixed Effects in Nonlinear Panel Data Models - Theory and Evidence
Multiple Fixed Effects in Nonlinear Panel Data Models - Theory and Evidence

... of panel data, and a significant literature now exists in econometric theory on the inclusion of fixed effects in both linear and nonlinear panel data models. The developed methods have also been put to use in various empirical studies. Many of these now include more than one fixed effect. However, ...
Vector Autoregressions with Parsimoniously Time Varying
Vector Autoregressions with Parsimoniously Time Varying

... the path of the parameter vector in a non parametric way. In this paper we assume the probability αT for an increment to be different from zero to depend on the sample length T , specifically αT = k α T −a , where k α and a are positive constants. In the case of a single variable this leads to an e ...
Vector Autoregressions with Parsimoniously Time
Vector Autoregressions with Parsimoniously Time

Lesson 8 Chapter 7: Confidence and Prediction Intervals
Lesson 8 Chapter 7: Confidence and Prediction Intervals

Springer Series in Statistics
Springer Series in Statistics

PRACTICE EXAMS
PRACTICE EXAMS

... 29. An analysis of credibility premiums is being done for a particular compound Poisson claims distribution, where the criterion is that the total cost of claims is within 5% of the expected cost of claims with a probability of 90%. It is found that with  ~  exposures (periods) and c ? ~  À, t ...
Statistics 1: MATH11400
Statistics 1: MATH11400

... Simple random samples Definition 1.4. We say that sample data values x1 , . . . , xn are the observed values of a of size n from the population if each sample member is chosen members, and each population member is ...
Likelihood-ratio-based confidence sets for the timing of structural
Likelihood-ratio-based confidence sets for the timing of structural

What Teachers Should Know about the Bootstrap: Resampling in
What Teachers Should Know about the Bootstrap: Resampling in

Syllabus 2008 - Institute of Cost Accountants of India
Syllabus 2008 - Institute of Cost Accountants of India

... A purse contains 1 rupee coin, 50 paisa coin, 25 paisa coin. The ratio of their numbers are x : y : z . The ratio of their values: (a) 4x: 2y : z (b) 2x : 3y : z (c) 4x: 3y : z (d)x : 2y : 4z Of the four numbers in proportion, if the product of two middle numbers is 48, the other numbers are : a) 32 ...
Quantifying the User Experience: Practical Statistics for User Research
Quantifying the User Experience: Practical Statistics for User Research

Download paper (PDF)
Download paper (PDF)

Training Manual on Sample Design for Surveys Draft 2006 Note
Training Manual on Sample Design for Surveys Draft 2006 Note

Sample Size Calculations
Sample Size Calculations

Bayesian Variable Selection in Normal Regression Models
Bayesian Variable Selection in Normal Regression Models

Kent Academic Repository
Kent Academic Repository

... Precise estimation of the number of follicles in ovaries is of key importance in the field of reproductive biology, both from a developmental point of view, where follicle numbers are determined at specific time points, as well as from a therapeutic perspective, determining the adverse effects of en ...
Nonparametric Regression Techniques in Economics
Nonparametric Regression Techniques in Economics

... a consequence, software which will handle such procedures in an automated fashion does not yet exist. A central objective of this paper is to demonstrate that these barriers are indeed substantially lower than might first appear. We comment on each in turn. First, we deal with the issue of theoretic ...
1.14 Polynomial regression
1.14 Polynomial regression

... where the εi ’s are iid with the N (0, σ 2 )-distribution. Then we can estimate the d + 1 parameters β0 , . . . , βd by least squares linear regression. Exercise 1.14.1. Download the dataset for this exercise and load it into R using read.table. You have a data frame with an x column and an y column ...
ch. 4 maximum entropy distributions
ch. 4 maximum entropy distributions

Model selection for estimating the non zero components of a
Model selection for estimating the non zero components of a

... where X = (X1 , . . . Xn )T is the vector of observations. The expectation of X, say m = (m1 , . . . , mn )T , and the variance τ 2 are unknown. Assuming that some of the components of m are equal to zero, our objective is to estimate the number of zero components as well as their positions. We prop ...
A Statistical Manual for Forestry Research
A Statistical Manual for Forestry Research

... of experiments, one may realize that the law of limiting factors operate in such cases which states that crop growth is constrained by the most limiting factor in the environment. The two main features of scientific method are its repeatability and objectivity. Although this is rigorously achieved i ...
1 2 3 4 5 ... 101 >

German tank problem



In the statistical theory of estimation, the problem of estimating the maximum of a discrete uniform distribution from sampling without replacement is known in English as the German tank problem, due to its application in World War II to the estimation of the number of German tanks.The analyses illustrate the difference between frequentist inference and Bayesian inference.Estimating the population maximum based on a single sample yields divergent results, while the estimation based on multiple samples is an instructive practical estimation question whose answer is simple but not obvious.
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