1. |
PITMAN MEDAL AWARDED TO E. J. HANNAN |
|
Australian Journal of Statistics,
Volume 33,
Issue 1,
1991,
Page 1-4
R.L. Tweedie,
Preview
|
PDF (324KB)
|
|
ISSN:0004-9581
DOI:10.1111/j.1467-842X.1991.tb00407.x
出版商:Blackwell Publishing Ltd
年代:1991
数据来源: WILEY
|
2. |
A SEMI‐MARKOV MODEL FOR EAR INFECTION |
|
Australian Journal of Statistics,
Volume 33,
Issue 1,
1991,
Page 5-16
C.A. McGlLCHRIST,
L. J. HlLLS,
Preview
|
PDF (495KB)
|
|
摘要:
SummaryA recent study of the prevalence of middle ear infection among Australian aborigines reports, for different age groups, the number currently infected, the number currently not infected and the number who are currently not infected but have scarring of the ear drum showing evidence of a previous infection. Incidence and recovery are modelled by a semi‐Markov model in which incidence of the infection is allowed to be nonstationar
ISSN:0004-9581
DOI:10.1111/j.1467-842X.1991.tb00408.x
出版商:Blackwell Publishing Ltd
年代:1991
数据来源: WILEY
|
3. |
A NOTE ON ASYMPTOTIC POSTERIOR NORMALITY FOR STOCHASTIC PROCESSES |
|
Australian Journal of Statistics,
Volume 33,
Issue 1,
1991,
Page 17-21
O.A. ADEKOLA,
Preview
|
PDF (196KB)
|
|
摘要:
SummaryIn a recent paper, Sweeting&Adekola (1987) presented a fairly general set of conditions for asymptotic posterior normality which covers a wide class of problems. In this paper we present an example of an explosive autoregressive model where our condition A4 does not hold.
ISSN:0004-9581
DOI:10.1111/j.1467-842X.1991.tb00409.x
出版商:Blackwell Publishing Ltd
年代:1991
数据来源: WILEY
|
4. |
VARIANCE ESTIMATION FOR SAMPLE AUTOCOVARIANCES: DIRECT AND RESAMPLING APPROACHES |
|
Australian Journal of Statistics,
Volume 33,
Issue 1,
1991,
Page 23-42
Clifford M. Hurvich,
Jeffrey S. Simonoff1,
Scott L. Zeger2,
Preview
|
PDF (947KB)
|
|
摘要:
SummaryThe usual covariance estimates for datan‐1from a stationary zero‐mean stochastic process {Xt} are the sample covariances Both direct and resampling approaches are used to estimate the variance of the sample covariances. This paper compares the performance of these variance estimates. Using a direct approach, we show that a consistent windowed periodogram estimate for the spectrum is more effective than using the periodogram itself. A frequency domain bootstrap for time series is proposed and analyzed, and we introduce a frequency domain version of the jackknife that is shown to be asymptotically unbiased and consistent for Gaussian processes. Monte Carlo techniques show that the time domain jackknife and subseries method cannot be recommended. For a Gaussian underlying series a direct approach using a smoothed periodogram is best; for a non‐Gaussian series the frequency domain bootstrap appears preferable. For small samples, the bootstraps are dangerous: both the direct approach and frequency domain jackknife are b
ISSN:0004-9581
DOI:10.1111/j.1467-842X.1991.tb00410.x
出版商:Blackwell Publishing Ltd
年代:1991
数据来源: WILEY
|
5. |
COMBINING TWO UNBIASED ESTIMATORS OF A COMMON MEAN OF TWO NORMAL POPULATIONS |
|
Australian Journal of Statistics,
Volume 33,
Issue 1,
1991,
Page 43-56
NUWAN NANAYAKKARA,
NOEL CRESSIE,
Preview
|
PDF (564KB)
|
|
摘要:
SummaryConsider estimating the common mean μ of two normal populations. Let () and () be the means and variances of two independent samples obtained from these populations. We give sufficient conditions for the choices of α1and α2in the unbiased estima
ISSN:0004-9581
DOI:10.1111/j.1467-842X.1991.tb00411.x
出版商:Blackwell Publishing Ltd
年代:1991
数据来源: WILEY
|
6. |
EXPONENTIAL DISPERSION MODELS AND THE GAUSS‐NEWTON ALGORITHM |
|
Australian Journal of Statistics,
Volume 33,
Issue 1,
1991,
Page 57-64
Gordon K. Smyth1,
Preview
|
PDF (332KB)
|
|
摘要:
SummaryIt is known that the Fisher scoring iteration for generalized linear models has the same form as the Gauss‐Newton algorithm for normal regression. This note shows that exponential dispersion models are the most general families to preserve this form for the scoring iteration. Therefore exponential dispersion models are the most general extension of generalized linear models for which the analogy with normal regression is preserved. The multinomial distribution is used as an exampl
ISSN:0004-9581
DOI:10.1111/j.1467-842X.1991.tb00412.x
出版商:Blackwell Publishing Ltd
年代:1991
数据来源: WILEY
|
7. |
ADJUSTING RESIDUALS IN ESTIMATION OF DISPERSION EFFECTS |
|
Australian Journal of Statistics,
Volume 33,
Issue 1,
1991,
Page 65-74
Subir Ghosh,
Yi‐Jing Duh1,
Preview
|
PDF (478KB)
|
|
摘要:
SummaryThis paper studies a method of adjusting the ordinary least squares residuals, when estimating and comparing dispersions, at various levels of factors in a replicated factorial experiment. Using a general dispersion model, theoretical results demonstrate the benefits of the method of adjusting residuals. An illustrative example is included.
ISSN:0004-9581
DOI:10.1111/j.1467-842X.1991.tb00413.x
出版商:Blackwell Publishing Ltd
年代:1991
数据来源: WILEY
|
8. |
SOME SECOND ORDER ASYMPTOTICS IN NONLINEAR REGRESSION |
|
Australian Journal of Statistics,
Volume 33,
Issue 1,
1991,
Page 75-84
Bo‐Cheng Wei1,
Preview
|
PDF (413KB)
|
|
摘要:
SummarySome asymptotics related to statistical curvature are studied from a geometric point of view. The method of stochastic expansion is used to study the second order information loss and some conditional inference for the least squares estimator in nonlinear regression in which the samples are independent but not necessarily identically distributed.
ISSN:0004-9581
DOI:10.1111/j.1467-842X.1991.tb00414.x
出版商:Blackwell Publishing Ltd
年代:1991
数据来源: WILEY
|
9. |
SPECTRAL REPRESENTATION AND ERGODICITY OF ASYMPTOTICALLY STATIONARY PROCESSES |
|
Australian Journal of Statistics,
Volume 33,
Issue 1,
1991,
Page 85-94
V.V. Anh,
K.E. Lunney1,
Preview
|
PDF (343KB)
|
|
摘要:
SummaryA second order process with mean zero and covariance isasymptotically stationaryif lim ds exists for every; this limit then defines the covariance function of the process. The paper establishes the spectral representation for the covariance function and a mean ergodic theorem for the process. When stationarity is assumed, the results reduce to the well‐known corresponding theorems for stationary processe
ISSN:0004-9581
DOI:10.1111/j.1467-842X.1991.tb00415.x
出版商:Blackwell Publishing Ltd
年代:1991
数据来源: WILEY
|
10. |
ON AN IDENTITY FOR FINDING MOMENTS OF SAMPLE MOMENTS OF BIVARIATE NORMAL RANDOM VARIABLES |
|
Australian Journal of Statistics,
Volume 33,
Issue 1,
1991,
Page 95-102
V.T. Prabhakaran,
V.K. Mahajan,
Preview
|
PDF (248KB)
|
|
摘要:
SummaryProbabilistic arguments are used to establish an identity useful for deriving the moments of the sample variances and covariance of a bivariate normal population. Some variances and covariances are derived to illustrate the use of the identity.
ISSN:0004-9581
DOI:10.1111/j.1467-842X.1991.tb00416.x
出版商:Blackwell Publishing Ltd
年代:1991
数据来源: WILEY
|