The Analysis of Two-Dimensional Stationary Processes with Discontinuous Spectra

Priestley, Mark

doi:10.2307/2334207

Cited by 10 publications

(13 citation statements)

References 3 publications

(7 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the statistics literature Priestley (1964) made early contributions towards an extension of HAC estimation for spatial processes within the context of estimating spectral densities of stationary random fields (with the index an element of Z 2 ). The theoretical econometrics literature relating to HAC estimators for spatially dependent data is relatively sparse.…”

mentioning

confidence: 99%

HAC estimation in a spatial framework

Kelejian

Prucha

2007

Journal of Econometrics

321

279

View full text Add to dashboard Cite

We suggest a nonparametric heteroscedasticity and autocorrelation consistent (HAC) estimator of the variance-covariance (VC) matrix for a vector of sample moments within a spatial context. We demonstrate consistency under a set of assumptions that should be satisfied by a wide class of spatial models. We allow for more than one measure of distance, each of which may be measured with error. Monte Carlo results suggest that our estimator is reasonable in finite samples. We then consider a spatial model containing various complexities and demonstrate that our HAC estimator can be applied in the context of that model. Jel classification: C12, C14,C21

show abstract

mentioning

confidence: 99%

HAC estimation in a spatial framework

Kelejian

Prucha

2007

Journal of Econometrics

321

279

View full text Add to dashboard Cite

show abstract

“…The above discussion suggested that the behaviour of R x (τ ) at large values of τ can be used as a discriminating tool for the issue at hand. In fact, Priestley was the first to propose a solution based on this property to detect the presence of harmonics in a time series [5,6]. We propose here a solution that is believed to be technically simpler.…”

Section: A Solution Based On Correlation Timementioning

confidence: 93%

“…Therefore requirement R2 is not met. Priestley has suggested an original procedure which apparently alleviates this trouble [5,6], but requirement R4 precludes its presentation here due to its high complexity.…”

Section: Approaches Based On Periodogram Statisticsmentioning

confidence: 99%

New Separation Techniques for Output‐Only Modal Analysis

Antoni

Garibaldi

Marchesiello

et al. 2004

Shock and Vibration

View full text Add to dashboard Cite

Caro Bruno, pensiamo sempre di vedere il tuo sorriso affacciato alla nostra porta, credendo di sentire i tuoi passi in corridoio: ci manchi.Abstract. The paper is devoted to the problem of discriminating between operational and natural modes of structures excited by generic inputs. This case often occurs when the system under analysis holds rotating parts and is contemporary excited by ambient noise; in this case the output-only techniques may fail being easily trapped in a misinterpretation of the system eigenvalues. A survey of the methods available in literature is given, together with the explanation of their failures. To solve this problem, two new techniques are introduced and their capabilities are checked with numerical and experimental data from a paper machine.

show abstract

“…However, if we try to estimate the coherency spectrum by substituting 'raw' estimates offxx(w),fyy(w) andfxy(w) into expression (8) then we will obtain a function which is one at all frequencies (Priestley 1981). The reason for this is that we will, in effect, be trying to calculate correlation coefficients using a single pair of observations at each frequency.…”

Section: Estimating Amplitude Phase Coherency and Gain Spectramentioning

confidence: 99%

The Exploratory Analysis of Bivariate Spatial Point Patterns Using Cross-Spectra

Mugglestone

Renshaw

1996

Environmetrics

View full text Add to dashboard Cite

SUMMARYWhereas frequency and time domain approaches to the analysis of temporal processes are regarded as complementary, the corresponding options for spatial processes, including spatial point processes, are less widely known. This paper concerns the spectral analysis of spatial point processes consisting of two types of events. The spectral functions needed for such an analysis are two-dimensional analogues of those used in the analysis of bivariate time series. We show how the spatial versions of co-, quadrature, amplitude, phase, coherency and gain spectra are defined and interpreted, and demonstrate the forms these functions take under various types of spatial dependence using simulated realizations of patterns with known structure. The potential of spectral analysis to recover information about complex anisotropic structure in environmental point patterns is illustrated using data on the movement of storms in the Sahel region of Africa.

show abstract

The Analysis of Two-Dimensional Stationary Processes with Discontinuous Spectra

Cited by 10 publications

References 3 publications

HAC estimation in a spatial framework

HAC estimation in a spatial framework

New Separation Techniques for Output‐Only Modal Analysis

The Exploratory Analysis of Bivariate Spatial Point Patterns Using Cross-Spectra

Contact Info

Product

Resources

About