Results 201 to 210 of about 91,295 (253)
Rosario: An algorithm to analyse cyclical data in Ecology. [PDF]
Biodivers Data JVelásquez-Roa T +3 more
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Geospatial variation and machine learning approaches to predict open defecation practice in Zambia. [PDF]
PLoS OneBirlie AA +10 more
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2011
This chapter discusses theoretical autocovariance, autocorrelation functions of autoregressive models of orders 1 and 2, and autocorrelation function-derived timescale. The autocorrelation function of a scalar time series is a prime tool for estimating the characteristic timescale separating successive independent realizations in ...
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This chapter discusses theoretical autocovariance, autocorrelation functions of autoregressive models of orders 1 and 2, and autocorrelation function-derived timescale. The autocorrelation function of a scalar time series is a prime tool for estimating the characteristic timescale separating successive independent realizations in ...
+8 more sources
Autocorrelation in Spaces [PDF]
Environment and Planning A: Economy and Space, 1979 Autocorrelation provides a means of characterising spatial structure, yet different kinds of structure are revealed in different spaces. The choice of weights when calculating an autocorrelation statistic is discussed. An examination of autocorrelation in transformed spaces is suggested and illustrated empirically by use of correlograms for German ...
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Communications in Statistics, 1975
Many time series in economics and other areas can be effectively represented as the sum of a polynomial trend and an autoregressive intagratad moving average process, in some cases after allowing for a systematic modal. Such series are nonstationary if either the degree $ill:a$eill: of the trend or the number d of autoregressive roots lying on the unit
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Many time series in economics and other areas can be effectively represented as the sum of a polynomial trend and an autoregressive intagratad moving average process, in some cases after allowing for a systematic modal. Such series are nonstationary if either the degree $ill:a$eill: of the trend or the number d of autoregressive roots lying on the unit
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Geographic Information Science & Technology Body of Knowledge, 2005
Spatial autocorrelation (SA)—the correlation among georeferenced observations arising from their relative locations in geographic space—has a history dating to the mid-1900s, although conceptual awareness of it dates back to the early 1900s. But SA is everywhere.
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Spatial autocorrelation (SA)—the correlation among georeferenced observations arising from their relative locations in geographic space—has a history dating to the mid-1900s, although conceptual awareness of it dates back to the early 1900s. But SA is everywhere.
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Spatial autocorrelation and political belonging autocorrelation
1997info:eu-repo/semantics ...
Grasland, C., Decroly, Jean-Michel
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Heteroskedasticity and Autocorrelation Corrections
2008Heteroskedasticity and autocorrelation consistent (HAC) covariance matrix estimation refers to calculation of covariance matrices that account for conditional heteroskedasticity of regression disturbances and serial correlation of cross products of instruments and regression disturbances.
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An analytical process of spatial autocorrelation functions based on Moran’s index
PLoS ONE, 2021Yanguang Chen
exaly