Using Spatiotemporal Methods to Fill Gaps In Energy Usage Interval Data


Autoria(s): Graves, Kristin K
Data(s)

27/05/2015

Resumo

Researchers analyzing spatiotemporal or panel data, which varies both in location and over time, often find that their data has holes or gaps. This thesis explores alternative methods for filling those gaps and also suggests a set of techniques for evaluating those gap-filling methods to determine which works best.

Formato

application/pdf

Identificador

http://academicworks.cuny.edu/hc_sas_etds/3

http://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1002&context=hc_sas_etds

Idioma(s)

English

Publicador

CUNY Academic Works

Fonte

School of Arts & Sciences Theses

Palavras-Chave #spatiotemporal #load research #geographically weighted regression #spatial regression #exploratory spatial data analysis #energy use #semivariogram #interpolation #temporal lag #Geographic Information Sciences #Geography #Longitudinal Data Analysis and Time Series #Multivariate Analysis #Oil, Gas, and Energy #Spatial Science #Statistical Models
Tipo

thesis