Bayesian Statistics (4th ed)
Page 36
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Whittaker, E. T., and Watson, G. N., A Course of Modern Analysis (4th edn), Cambridge: Cambridge University Press (1927).
Williams, J. D., The Compleat Strategyst, Being a Primer on the Theory of Games of Strategy (2nd edn), New York: McGraw-Hill (1966) [1st edn (1954)].
Wilson, E. B., An Introduction to Scientific Research, New York: McGraw-Hill (1952).
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Index
ABC algorithm
ABC-MCMC
ABC-PRC
ABC-SMC
local linear regression
model selection
neural network
rejection
Absolute error loss
Acceptance-rejection sampling
Action
Addition law, generalized
Admissibility
Alternative hypothesis
Analysis of variance
Ancillary
ANOVA
Antilogarithm
Approximate Bayesian computation
Arc-sine distribution
ARMA
Autoregressive chains
Baseball
Bayes linear methods
Bayes, Rev. Thomas
estimator
factor
postulate
risk
rule
theorem
Bayesian confidence interval
Bayesian decision theory
Behrens’ distribution
Behrens-Fisher problem
Benford’s Law
Bernardo, J.M.
Bernoulli trials
Beta distribution
Beta-binomial distribution
Beta-Pascal distribution
Bilateral bivariate Pareto distribution
Binomial distribution
Bivariate density
Bivariate normal distribution
BUGS
Calculus of variations
Candidate density
Cardioid distribution
Cauchy distribution
Censorship
Central limit theorem
Change of variable rule
Change point
Characteristic function
Chebyshev, P. L. (Čebyšev, P. L.)
Chest measurements
Chi-squared distribution
non-central
Choleski factorization
Circular normal distribution
Classical statistics
Coagulation time
Coal
coda
Components of variance model
Composite hypothesis
Conditional density
Conditional distribution function
Conditional expectation
Conditional variance
Conditionality principle
weak
Conditionally conjugate prior
Confidence interval
Bayesian
Conjugate gamma distribution
Conjugate prior
mixture of
Contingency table
Continuous random variable
Contrast
Convergence of Markov chains
Conversation, Extension of the
Correlation coefficient
sample
Covariance
Cramèr-Rao bound
Credible interval
Cumulative distribution function
Data augmentation
chained
Data translated likelihood
Decision rule (function)
Decision theory
Defender’s fallacy
Density
bivariate
candidate
conditional
improper
joint
marginal
proper
Dependent variable
Design of experiments
Detailed balance
Detailed balance equation
Digamma function
Discrete random variable
Discrete uniform distribution
Discrimination
Distribution function
conditional
invariant
joint
stationary
Dominant likelihood
Dominate
DoodleBUGS
Doog, K. Caj
Drunken soldier
Elementary event
EM algorithm
generalized
Empirical Bayes method
estimator
Entropy
Epanechnikov kernel
ESP
Estimator
admissible
Bayes
Efron-Morris
empirical Bayes
James-Stein
maximum likelihood
MVUE
point
`pre-test’
shrinkage
unbiased
Event
elementary
Events, independent
Evidence
weight of
Exact significance level
Exchangeability
Expectation
conditional
Experiment
mixed
Experiments, design of
Explanatory variable
Exponential distribution
Exponential family
Extension of the conversation
Extensive form
Extra-sensory perception
F distribution
Factorization Theorem
Fallacies (prosecutor’s, etc.)
First digit
Fish
Fisher’s information
Fisher, Sir Ronald Aylmer
Fisher-Behrens problem
Forecasting
Game
Gamma distribution
conjugate
GEM algorithm
General linear model
Generalized addition law
Generalized inverse
Generalized linear model
Generalized multiplication law
Genetics
linkage
Geometric distribution
Geyser
Old Faithful
Geyser, Old Faithful
Gibbs sampler
GLM
Greek data
Haar prior
Haldane’s prior
Hay
HDR
Helmert transformation
Hepatitis B
Hierarchical
prior
Hierarchical model
normal
Highest density region
Homoscedastic
Horse kicks
Hyperbolic tangent
Hypergeometric distribution
Hyperparameter
Hyperprior
Hypothesis
alternative
composite
null
simple
testing
 
; testing, one sided
i.i.d.
Image restoration
Importance function
Importance sampling
Improper prior
Inadmissible
Independence chains
Independent events
Independent random variables
Indicator function
Information
Informative stopping rule
Intelligence test
Intercept
Invariant distribution
Invariant prior
Inverse chi distribution
Inverse chi-squared distribution
Inverse root-sine transformation
Iterated logarithm
Jacobian
Jeffreys, Sir Harold
paradox
principle
prior
rule
Jumping distribution
King’s Arms
Kullback-Leibler
Laplace’s rule of succession
Laplace, Pierre-Simon, Marquis de
Layout, one way
Layout, two way
Least squares
Likelihood
data translated
dominant
maximum
nearly constant
principle
ratio
standardized
Likelihood-free computation
Limericks
Lindley, D. V.
method
paradox
Line of best fit
Line, regression
Linear Bayes methods
Linear model
general
Linkage, genetic
Log chi-squared distribution
Log tables
Log-likelihood
Log-odds
ratio
Logistic distribution
Logistic regression
Loom
Loss
absolute error
quadratic
weighted quadratic
zero-one
MAD
Marginal density
Markov chain
convergence
periodic
reducible
Markov Chain Monte Carlo
Maximum
Maximum likelihood
Maxwell distribution
MCMC
RJMCMC
Mean
absolute deviation
square error
Median
Mendel
Method of scoring
Metropolis within Gibbs
Metropolis-Hastings algorithm
Mice
Minimal sufficient statistic
Minimum
Minimum variance unbiased estimator
Minitab
Misprints
Mixed experiment
Mixed random variables
Mixture of conjugate priors
Modal interval
Mode
posterior
Model
components of variance
general linear
hierarchical
hierarchical normal
linear
one way
random effects
two way
Monte Carlo methods
Moving, probability of
Multiple regression
Multiplication law, generalized
Multivariate estimation
Multivariate normal distribution
Multivariate t distribution
MVUE
Negative binomial distribution
Negative exponential distribution
Newton-Raphson method
Neyman’s Factorization Theorem
Neyman-Pearson theory
Nitrogen
Non-central chi-squared distribution
Nonparametric methods
Normal distribution
bivariate
circular
multivariate
variance
wrapped
Normal form
Normal/chi-squared distribution
Nuisance parameter
Nuisance parameters
Null hypothesis
point
sharp
Numerical methods
Odds
ratio
Old Faithful geyser
One way model (layout)
One-sided test
OpenBUGS
Optional (optimal) stopping
Order statistic
P-value
Paired comparison
Parameter space
Pareto distribution
bilateral bivariate
Pareto optimality
Patil’s approximation
Penicillin
Petersburg paradox
Point estimator
Point null hypothesis
Poisson distribution
Pólya distribution
Polynomial regression
Posterior
reference
Posterior mode
Posterior odds
Posterior probability
Precision
Predictive distribution
Preposterior distribution
Prior
conditionally conjugate
conjugate
diffuse
Haar
Haldane’s
hierarchical
improper
invariant
Jeffreys’
odds
probability
proper
reference
semi-conjugate
uniform
vague
Probability
density
element
posterior
prior
unconditional
Probability of moving
Proposal distribution
Prosecutor’s fallacy
Pseudo-random numbers
Pumps
Quadratic loss
Quartile
R2OpenBUGS
R2WinBUGS
Radiocarbon
Rainfall
Random digits
Random effects model
Random variables
continuous
discrete
independent
mixed
uncorrelated
Random walk chains
Rats
Rectangular distribution
Recursive construction
Reference posterior
Reference prior
Regression
line
multiple
polynomial
recursive
ridge
Rejection region
Rejection sampling
Ridge regression
Risk function
RJMCMC
Roberts, H. V.
Robustness
Rocks
St Petersburg paradox
Sample correlation coefficient
Sampling
importance
importance resampling
rejection
Sampling importance resampling
Sampling theory statistics
Savage, L. J.
Scab disease
Schlaifer, R.
Score
Scoring, method of
Semi-conjugate prior
Semi-interquartile range
Sensitivity analysis
Sequential methods
Sequential use of Bayes’ Theorem
Sharp null hypothesis
Simple hypothesis
Simpson’s rule
SIR algorithm
Size
Skewness
Slope
Soldier, drunken
`Speed of light’ question
St Petersburg paradox
Standard deviation
Standardized likelihood
St
ate space
Stationary distribution
Statistic
minimal sufficient
order
sufficient
Statistical decision problem (game)
Stein estimator
Stopping rule
informative
principle
Structural relationship
`Student’ (W.S. Gosset)
Student’s t distribution
multivariate
Sufficiency
Sufficiency principle
weak
Sufficient statistic
Support
t distribution
multivariate
tanh
Taylor’s Theorem
Tchebycheff, P. L.
Tea consumption
Time reversibility
Time series
Toxoplasmosis
Trace
Traffic accidents
Tramcar
Travelling salesman problem
Trigamma function
Trinomial distribution
Twins
Two by two table
Two way model (layout)
Two-sample problem
Type I and Type II errors
Unbiased
Unconditional Probability
Uncorrelated
Uniform distribution
discrete
Uniform prior
Utility
Variables
dependent
explanatory
independent
random
Variance
analysis of
conditional
normal
ratio
Variance-covariance matrix
Variance-stabilizing transformation
Variational Bayes
Variations, calculus of
von Mises’ distribution
W and Z particles
Water
Weak conditionality principle
Weak sufficiency principle
Weight of evidence
Weighted quadratic loss
Wheat
WinBUGS
Window
Wishart distribution
Wrapped normal distribution
z distribution
Zero-one loss
Zipf’s Law