Linked Life Data

1726712

Source:http://linkedlifedata.com/resource/pubmed/id/1726712

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
1992-10-22
pubmed:abstractText
When profiles of activity patterns are used to generate time series of simulated exposure, one typically samples from exposure distributions which are microenvironment-specific to each activity. If the simulation time step is short, then independent sampling at each time step, ignoring autocorrelation, will result in aggregates with too little variability from one simulation to another. Autocorrelation can often be modeled with one or two extra parameters and then used in the simulation. Furthermore, one may substantially reduce computation by generating a single averaged exposure for each activity segment whose distribution depends in a simple way on the activity duration and the modeled autocorrelation. The process is illustrated using the El Camino Real commuting exposure study data of Ott, Switzer, and Willits.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
1053-4245
pubmed:author
pubmed:issnType
Print
pubmed:volume
1
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
109-21
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1991
pubmed:articleTitle
Averaging time modeling of exposure simulation with application to the El Camino Real vehicle data.
pubmed:affiliation
Department of Statistics, Stanford University, CA 94305.
pubmed:publicationType
Journal Article