|
1. |
Reliability analysis of repairable systems from in–service failure count data |
|
Applied Stochastic Models and Data Analysis,
Volume 10,
Issue 3,
1994,
Page 141-151
R. Calabria,
M. Guida,
G. Pulcini,
Preview
|
PDF (676KB)
|
|
摘要:
AbstractPoint maximum likelihood estimators for parameters, mean number of failures, and failure rate in a non–homogeneous Poisson process are derived, when only count data fromkidentical processes are available. Approximate confidence intervals based on the parametric bootstrap technique are considered. The performances of both the point and interval estimation procedures are assessed via Monte Carlo simulatio
ISSN:8755-0024
DOI:10.1002/asm.3150100302
出版商:John Wiley&Sons, Ltd.
年代:1994
数据来源: WILEY
|
2. |
Time series analysis for ground penetrating radar (GPR) asphalt thickness profile |
|
Applied Stochastic Models and Data Analysis,
Volume 10,
Issue 3,
1994,
Page 153-167
B. Nii. Attoh‐Okine,
Preview
|
PDF (593KB)
|
|
摘要:
AbstractTime series obtained from the waveform profiles of the ground penetrating radar (GPR) thickness of the asphaltic concrete layers of in–service pavement holds a key to the understanding of thickness variation and the presence of cavities within and below the pavement surface. In this paper, the fundamental techniques of time series modelling—(i) identification, (ii) estimation and (iii) diagnostics—are applied to the GPR thickness profile of three types of pavement—(a) fully–designed (b) partially–designed and (c) compositely designed pavement. Actual applications are made using data from in–service pavement in the state of Kansas. The main purpose of this study is to investigate the mechanism that drives the data and to compare the model errors and statistics of the thickness profiles of different types of flexible pavement. In the present study, the time series is replaced by a distance scale, but the name time serie
ISSN:8755-0024
DOI:10.1002/asm.3150100303
出版商:John Wiley&Sons, Ltd.
年代:1994
数据来源: WILEY
|
3. |
Evaluating departures from fair representation |
|
Applied Stochastic Models and Data Analysis,
Volume 10,
Issue 3,
1994,
Page 169-185
Z. Bondarczuk,
T. Kowalczyk,
E. Pleszczyńska,
W. Szczesny,
Preview
|
PDF (909KB)
|
|
摘要:
AbstractComputer–intensive estimates are introduced to evaluate departures from proportionality between the numbers of electors in a partition of a voting population and the numbers of representatives in the corresponding partition of the elected representation. At the first stage a pair of indices is proposed, one to evaluate the total strength of the departures and the other to indicate to what extent they are due to over–representation increasing (or decreasing) with the number of electors in a group. The properties of the indices are examined in suitably defined stochastic models which describe this type of over–representation. Since the values of the indices are strongly influenced by the distribution of electors in the given partition, a second stage of estimation is performed in order to get some [partition–free] information on the existence of a monotone size representation, and, if it exists, on its strength. The relevant transformation is based on intensive computer simulation in the introduced models. The methods proposed are applied to the results of the 1991 election of the Polish Scientific Research Council, which distributes funds among universities, scientific institutions and individual groups of rese
ISSN:8755-0024
DOI:10.1002/asm.3150100304
出版商:John Wiley&Sons, Ltd.
年代:1994
数据来源: WILEY
|
4. |
A systems approach to the calibration of deterministic dynamic nonlinear simultaneous equation models with incomplete data |
|
Applied Stochastic Models and Data Analysis,
Volume 10,
Issue 3,
1994,
Page 187-214
Michael J. Hartley,
Preview
|
PDF (1826KB)
|
|
摘要:
AbstractThis paper develops an interactive three–stage systems approach for the calibration of the structural parameters and missing data within a deterministic, dynamic non–linear simultaneous equations model under arbitrary configurations of incomplete data. In Stage One, we minimize a quadratic loss function in the differences between the actual endogenous variables and the predicted solution values, relative to any feasible choice of the structural parameters. Missing exogenous variables and initial endogenous variables are treated as additional parameters to be calibrated; whereas missing current endogenous variables are treated by the missing data updating condition, in which the current solution values iteratively and sequentially replace those absent. Stage One may or may not lead to unique calibrations of the structural parameters—a fact that can be monitoreda posterioriusing singular value decompositions of the relevant Jacobian matrix. If not, there is an equivalence class of parameter values, all of which result in the same loss function value. If Stage Two is necessary, we attempt to exploit the non–linearity and simultaneity of the structural system to extract further information about the parameters from the same database, by minimizing the distance between the restricted and unrestricted reduced forms, while constraining the parameters also to lie within the Stage One equivalence class. This requires the use of higher–order numerical derivatives, and probably restricts its use in all but the simplest of cases to the next generation of supercomputers with massive numbers of parallel processors and much larger word–sizes. In Stage Three, various methods by which the original structural model can be simplified, given a non–unique Stage One calibration, ar
ISSN:8755-0024
DOI:10.1002/asm.3150100305
出版商:John Wiley&Sons, Ltd.
年代:1994
数据来源: WILEY
|
5. |
Non–parametric probability density function estimation on a bounded support: Applications to shape classification and speech coding |
|
Applied Stochastic Models and Data Analysis,
Volume 10,
Issue 3,
1994,
Page 215-231
S. Saoudi,
A. Hillion,
F. Ghorbel,
Preview
|
PDF (685KB)
|
|
摘要:
AbstractIn statistics, it is usually difficult to estimate the probability density function fromNindependent samplesX1,X2, …︁,XNidentically distributed. A lot of work has been done in the statistical literature on the problem of probability density estimation (e.g. Cencov, 1962; Devroye and Gyorfi, 1981; Hall, 1980 and 1982; Hominal, 1979; Izenman, 1991; Kronmal and Tarter, 1968; Parzen, 1962; Rosenblatt, 1956). In this paper, we consider random variables on bounded support. Orthogonal series estimators, studied in detail by Kronmal and Tarter (1968), by Hall (1982) and by Cencov (1962), show that there is a disadvantage related to the Gibbs phenomenon on the bias of these estimators. We suggest a new method for the non–parametric probability density function estimation based on the kernel method using an appropriately chosen regular change of variable. The new method can be used for several problems of signal processing applications (scalar or vector quantization, speech or image processing, pattern recognition, etc.). Applications to shape classification and speech coding are
ISSN:8755-0024
DOI:10.1002/asm.3150100306
出版商:John Wiley&Sons, Ltd.
年代:1994
数据来源: WILEY
|
6. |
Masthead |
|
Applied Stochastic Models and Data Analysis,
Volume 10,
Issue 3,
1994,
Page -
Preview
|
PDF (16KB)
|
|
ISSN:8755-0024
DOI:10.1002/asm.3150100301
出版商:John Wiley&Sons, Ltd.
年代:1994
数据来源: WILEY
|
|