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Hamilton J.D. — Time Series Analysis
Hamilton J.D. — Time Series Analysis



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Íàçâàíèå: Time Series Analysis

Àâòîð: Hamilton J.D.

Àííîòàöèÿ:

The last decade has brought dramatic changes in the way that researchers analyze time series data. This much-needed book synthesizes all of the major recent advances and develops a single, coherent presentation of the current state of the art of this increasingly important field. James Hamilton provides for the first time a thorough and detailed textbook account of important innovations such as vector autoregressions, estimation by generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, Hamilton presents traditional tools for analyzing dynamic systems, including linear representations, autocovariance, generating functions, spectral analysis, and the Kalman filter, illustrating their usefulness both for economic theory and for studying and interpreting real-world data. This book is intended to provide students, researchers, and forecasters with a definitive, self-contained survey of dynamic systems, econometrics, and time series analysis. Starting from first principles, Hamilton's lucid presentation makes both old and new developments accessible to first-year graduate students and nonspecialists. Moreover, the work's thoroughness and depth of coverage will make Time Series Analysis an invaluable reference for researchers at the frontiers of the field. Hamilton achieves these dual objectives by including numerous examples that illustrate exactly how the theoretical results are used and applied in practice, while relegating many details to mathematical appendixes at the end of chapters. As an intellectual roadmap of the field for students and researchers alike, this volume promises to be the authoritative guide for years to come.


ßçûê: en

Ðóáðèêà: Ìàòåìàòèêà/

Ñòàòóñ ïðåäìåòíîãî óêàçàòåëÿ: Ãîòîâ óêàçàòåëü ñ íîìåðàìè ñòðàíèö

ed2k: ed2k stats

Ãîä èçäàíèÿ: 1994

Êîëè÷åñòâî ñòðàíèö: 820

Äîáàâëåíà â êàòàëîã: 14.09.2007

Îïåðàöèè: Ïîëîæèòü íà ïîëêó | Ñêîïèðîâàòü ññûëêó äëÿ ôîðóìà | Ñêîïèðîâàòü ID
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Ïðåäìåòíûé óêàçàòåëü
Leverage effect      668
Lewis, Craig M.      672
Li, W.K.      127
Likelihood function      746—747 see
Likelihood function concentrating      638
Likelihood function, vector autoregression and      291—294 310—311
Likelihood ratio test      144—145 296—298 648—650
Lilien, David M.      667 672
LIMIT      see "Convergence"
Linear dependence      728—729
Linear dependence, Geweke's measure of      313—314
Linear projection, forecasts and      74—76 92—100
Linear projection, multivariate      75
Linear projection, ordinary least squares regression and      75—76 113—114
Linear projection, properties of      74—75
Linear projection, updating      94
Linear regression      see also "Generalized least squares (GLS)" "Generalized "Ordinary
Linear regression, algebra of      200—202
Linear regression, review of OLS and i.i.d.      200—207
Linearly deterministic      109
Linearly indeterministic      109
Litterman, Robert B.      360—362 402—403
Ljungqvist, Lars      305 447 653
Lo, Andrew W.      449 531 532
Local identification      334 388
Local maximum      134 137 226
Logarithms      717—718
Long-run effect      6—7
Loretan, Mico      608 613
Loss function      72
Lucas, Robert E., Jr.      306
Luetkepohl, Helmut      336 339
MA      see "Moving average"
MacKinlay, A. Craig      531 532
Maddala, G.S.      250
Magnus, Jan R.      302 317 318 704
Makov, U.E.      689
Malinvaud, E.      411
Malliaris, A.G.      479
Mankiw, N. Gregory      361 444
Mark, Nelson      664
Markov chain      678
Markov chain, absorbing state      680
Markov chain, ergodic      681—682
Markov chain, forecasting      680
Markov chain, periodic      685
Markov chain, reducible      680
Markov chain, transition matrix      679
Markov chain, two-state      683—684
Markov chain, vector autoregressive representation      679
Marsden, Jerrold E.      196 704
Martin, R.D.      127
Martingale difference sequence      189—190 193—195
Matrix/matrices, adjoint      727
Matrix/matrices, conjugate transposes      734—735
Matrix/matrices, determinant      724—727
Matrix/matrices, diagonal      721
Matrix/matrices, duplication      301
Matrix/matrices, gain      380
Matrix/matrices, geometric series      732
Matrix/matrices, Hessian      139 736
Matrix/matrices, idempotent      201
Matrix/matrices, identity      722
Matrix/matrices, information      143—144 429
Matrix/matrices, inverse      727—728
Matrix/matrices, Jacobian      737
Matrix/matrices, Jordan decomposition      730—731
Matrix/matrices, lower triangular      725
Matrix/matrices, nonsingular      728
Matrix/matrices, optimal weighting      412—414
Matrix/matrices, partitioned      724
Matrix/matrices, positive definite      733—734
Matrix/matrices, positive semidefinite      733
Matrix/matrices, power of      722
Matrix/matrices, singular      728
Matrix/matrices, square      721
Matrix/matrices, symmetric      723
Matrix/matrices, trace of      723—724
Matrix/matrices, transition      679
Matrix/matrices, transposition      723
Matrix/matrices, triangular      729
Matrix/matrices, triangular factorization      87
Matrix/matrices, upper triangular      727
Maximum likelihood estimation (MLE)      117 747 see
Maximum likelihood estimation (MLE), asymptotic properties of      142—145 429—430
Maximum likelihood estimation (MLE), concentrated      638
Maximum likelihood estimation (MLE), conditional      122 125—126
Maximum likelihood estimation (MLE), EM algorithm and      688—689
Maximum likelihood estimation (MLE), full-information maximum likelihood      247—250
Maximum likelihood estimation (MLE), Gaussian AR process and      118—127
Maximum likelihood estimation (MLE), Gaussian ARMA process and      132—133
Maximum likelihood estimation (MLE), Gaussian MA process and      127—131
Maximum likelihood estimation (MLE), general coefficient constraints and      315—318
Maximum likelihood estimation (MLE), global maximum      134 137
Maximum likelihood estimation (MLE), GLS and      222
Maximum likelihood estimation (MLE), GMM and      427—431
Maximum likelihood estimation (MLE), Kalman filter and      385—389
Maximum likelihood estimation (MLE), local      134 137
Maximum likelihood estimation (MLE), prediction error decomposition      122 129
Maximum likelihood estimation (MLE), regularity conditions      427 698
Maximum likelihood estimation (MLE), standard errors for      143—144 429—430
Maximum likelihood estimation (MLE), statistical inference with      142—145
Maximum likelihood estimation (MLE), vector autoregression and      291—302 309—318
Maximum likelihood estimation (MLE), Wald test for      429—430
McCurdy, Thomas H.      691
McLeod, A.I.      127
Mean square, convergence in      182—183 749
Mean squared error (MSE)      73
Mean squared error (MSE) of linear projection      74 75 77
Mean, ergodic for the      47
Mean, population      739
Mean, sample      186—195 279—285 740—741
Mean, unconditional      44
Mean-value theorem      196
Meese, Richard      305
Milhoj, Anders      662 670
Miller, H.D.      681 685
Mixingales      190—192
Mixture distribution      685—689
MLE      see "Maximum likelihood estimation (MLE)"
Modulus      709
Moments      see also "Generalized method of moments (GMM)"
Moments, population      739—740 744—745
Moments, posterior      363—365
Moments, sample      740—741
Moments, second      45 92—95 192—193
Monahan, J. Christopher      284 285 618
Money demand      1 324
Monfort, A.      431 670
Monte Carlo method      216 337 365—366 398
Moore, John B.      47 373 403
Mosconi, Rocco      650
Moving average (MA), cointegration and      574—575
Moving average (MA), first order      48—49
Moving average (MA), forecasting      82—83 95—98
Moving average (MA), infinite order      51—52
Moving average (MA), maximum likelihood estimation for Gaussian      127—131 387
Moving average (MA), parameter estimation      132 387
Moving average (MA), population spectrum for      154—155 276
Moving average (MA), qth order      50—51
Moving average (MA), sums of      102—107
Moving average (MA), vector      262—264
MSE      see "Mean squared error (MSE)"
Mustafa, C.      672
Muth, John F.      440
Nason, James A.      361
Nelson, Charles R.      109 253 426 444 504
Nelson, Daniel B.      662 666 667 668 672
Nelson, Harold L.      126
Nerlove, Mark      671
Neudecker, Heinz      302 704
Newbold, Paul      557
Newey — West estimator      220 281—282
Newey, Whitney K.      220 281—282 284 414
Newton — Raphson      138—139
Ng, Victor K.      668 671 672
Nicholls, D.F.      218
Noh, Jason      672
Nonparametric estimation      see also "Kernel"
Nonparametric estimation, bandwidth      165 671
Nonparametric estimation, conditional variance and      671
Nonparametric estimation, cross validation      671
Nonparametric estimation, population spectrum      165—167
Nonsingular      728
Nonstochastic      739
Normal distribution      745—746 748—749 751—752
Normalization, cointegration and      589
Numerical optimization, convergence criterion      134 137
Numerical optimization, Davidon — Fletcher — Powell      139—142
Numerical optimization, EM algorithm      688—689 696
Numerical optimization, grid search      133—134
Numerical optimization, inequality constraints      146—148
Numerical optimization, Newton — Raphson      138—139
Numerical optimization, numerical maximization      133 146
Numerical optimization, numerical minimization      142
Numerical optimization, steepest ascent      134—137
O'Nan, Michael      203 704
Observation equation      373
Ogaki, Masao      424 573 575 618 651
Ohanian, Lee E.      554
Oil prices, effects of      307—308
OLS      see "Ordinary least squares"
Operators, annihilation      78
Operators, first-difference      436
Operators, time series      25—26
Option prices      672
Order in probability      460
Ordinary least squares (OLS)      see also "Generalized least squares (GLS)" "Hypothesis "Regression"
Ordinary least squares (OLS), algebra of      75—76 200—202
Ordinary least squares (OLS), autocorrelated disturbances      217 282—283
Ordinary least squares (OLS), chi-square test      213
Ordinary least squares (OLS), distribution theory      209 432—433
Ordinary least squares (OLS), estimated coefficient vector      202—203
Ordinary least squares (OLS), F test      205—207
Ordinary least squares (OLS), GMM and      416—418
Ordinary least squares (OLS), heteroskedasticity      217 282—283
Ordinary least squares (OLS), linear projection and      75—76 113—114
Ordinary least squares (OLS), non-Gaussian disturbances      209
Ordinary least squares (OLS), t test      204 205
Ordinary least squares (OLS), time trends and      454—460
Orthogonal      743
Orthogonality conditions      411
Orthogonalized impulse-response function      322
Ouliaris, Sam      573 593 601 630
Outer-product estimate      143
Pagan, A.R.      218 389 668 671 672
Pantula, S.G.      532 670
Park, Joon Y.      214 483 532 547 549 573 575 601 618 651
Partial autocorrelation, population      111—112
Partial autocorrelation, sample      111—112
Parzen kernel      283
Pearce, Douglas K.      305
Period      708
Periodic      707
Periodic Markov chain      685
Periodogram, multivariate      272—275
Periodogram, univariate      158—163
Permanent income      440
Perron, Pierre      449 475 506—516
Phase      275 708
Phillips triangular representation      576—578
Phillips — Ouliaris — Hansen tests      599
Phillips — Perron tests      506—514 762—763
Phillips, G.D.A.      386
Phillips, Peter C.B.      195 214 475 483 487 506—516 532 533 534 545 547 549 554 557 576—578 587 593 601 608 613—618 630 650 651
Pierce, David A.      305
Plim      181 749
Ploberger, Werner      698
Plosser, Charles I.      444 573
Polar coordinates      704—705 710
Polynomial in lag operator      27 258
Population, canonical correlations      630—633
Population, coherence      275
Population, correlation      743
Population, covariance      742
Population, moments      739—740 744—745
Population, spectrum      61—62 152—157 163—167 269 276—277
Port, Sidney C.      749
Porter-Hudak, Susan      449
Posterior density      352
Powell, M.J.D.      139—142
Power series      714
PRECISION      355
Predetermined      238
Prediction error decomposition      122 129 310
Present value      4 19—20
Principal diagonal      721
Prior distribution      351
Probability limit      181 749
pth-order autoregressive process      58—59
pth-order difference equations      7—20 33—36
Pukkila, Tarmo      133
Purchasing power parity      see "Exchange rates"
qth-order moving average      50—51
Quadratic equations      710—711
Quadratic spectral kernel      284
Quadrature spectrum      271
Quah, Danny      335
Quandt, Richard E.      142
Quasi-maximum likelihood estimate      126 145 430—431
Quasi-maximum likelihood estimate, ARCH      663—664
Quasi-maximum likelihood estimate, GLS      222
Quasi-maximum likelihood estimate, GMM and      430—431
Quasi-maximum likelihood estimate, Kalman filter and      389
Quasi-maximum likelihood estimate, standard errors      145
RADIANS      704
Ramage, J.G.      216
Random variable      739
Random walk      436
Random walk OLS estimation      486—504
Rao, C.R.      52 183 184 204
Rappoport, Peter      449
Rational expectations      422
Rational expectations, efficient markets hypothesis      306
Raymond, Jennie      664
Real interest rate      376
Real number      708
Recessions      167—168 307—308 450 697—698
Recursive substitution      1—2
Reduced form      245—246 250—252
Reduced form, VAR      327 329
Reducible Markov chain      680
Regime-switching models, Bayesian estimation      689
Regime-switching models, derivation of equations      692—693
Regime-switching models, description of      690—691
Regime-switching models, EM algorithm      696
Regime-switching models, maximum likelihood      692 695—696
Regime-switching models, singularity      689
Regime-switching models, smoothed inference and forecasts      694—695
Regression      see also "Generalized least squares (GLS)" "Generalized "Ordinary
Regression, classical assumptions      202
Regression, time-varying parameters      400
Regularity conditions      427 698
Reichlin, Lucrezia      449
Reinsel, G.C.      601 630
Residual sum of squares (RSS)      200
Rich, Robert W.      664
Ridge regression      355
Rissanen, J.      133
Robins, Russell P.      667 672
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