Some Basic Theory for Statistical Inference
Regular price
€198.40
14 days return policy
Shipping & Delivery
A01=E.J.G. Pitman
advanced statistical inference methods
Age Group_Uncategorized
Age Group_Uncategorized
asymptotic efficiency
Asymptotic Power
Asymptotic Relative Efficiency
Author_E.J.G. Pitman
automatic-update
Category1=Non-Fiction
Category=PBT
Conditional Distributions
Continuous Distribution Function
Continuous Probability Measure
COP=United Kingdom
cramer-rao inequality
Delivery_Pre-order
Discrete Probability Measure
Discrete Probability Space
Discrete Sample Space
Dispersion Matrix
Distribution Function
eq_isMigrated=2
eq_nobargain
Glivenko Cantelli Theorem
Independent Uniform Random Variables
Language_English
Lebesgue Measure
Left Hand Derivative
likelihood principle
Likelihood Ratio
measure
Negative Binomial Families
Neyman Pearson Theorem
PA=Temporarily unavailable
Posterior Distributions
Price_€100 and above
probability
Probability Measure
probability measures
PS=Active
Real Valued Statistic
Sample Distribution Function
Sample Path
sensitivity analysis statistics
softlaunch
Sufficient Regularity Conditions
sufficient statistics
Product details
- ISBN 9781315897677
- Weight: 380g
- Dimensions: 138 x 216mm
- Publication Date: 29 Nov 2017
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Hardback
- Language: English
Secure
checkout
Fast Shipping
Easy returns
In this book the author presents with elegance and precision some of the basic mathematical theory required for statistical inference at a level which will make it readable by most students of statistics.
