Asymptotics, Nonparametrics, and Time Series
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advanced time series modeling applications
ARMA Model
Asymptotic Relative Efficiencies
Asymptotically Normal
Autoregressive Models
Bayesian estimation techniques
Category=PBK
Category=PBT
central
Data Set
density
dirichlet
Dirichlet Process
distribution
Distribution Function
Edgeworth Expansions
empirical Fourier analysis
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Follow
Hellinger Distance
hypothesis
Iid Random Variables
IJ
Innovation Density
IRI
Linear Rank Statistics
local
Markov chain analysis
Martingale Central Limit Theorem
Maximum Likelihood Estimator
Multistep Prediction
multivariate regression models
Nonparametric Functional Estimation
normality
North Holland Publishing Company
Nuisance Parameter
Posterior Distribution
process
spectral
spectral density estimation
statistical inference methods
Time Series
Transition Distribution
Weak Convergence
Product details
- ISBN 9780824700515
- Weight: 1288g
- Dimensions: 156 x 234mm
- Publication Date: 18 Feb 1999
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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"Contains over 2500 equations and exhaustively covers not only nonparametrics but also parametric, semiparametric, frequentist, Bayesian, bootstrap, adaptive, univariate, and multivariate statistical methods, as well as practical uses of Markov chain models."
Subir Ghosh
