27 research outputs found

    Area estimation using multiyear designs and partial crop identification

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    Progress is reported for the following areas: (1) estimating the stratum's crop acreage proportion using the multiyear area estimation model; (2) assessment of multiyear sampling designs; and (3) development of statistical methodology for incorporating partially identified sample segments into crop area estimation

    Missing observations in multiyear rotation sampling designs

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    Because Multiyear estimation of at-harvest stratum crop proportions is more efficient than single year estimation, the behavior of multiyear estimators in the presence of missing acquisitions was studied. Only the (worst) case when a segment proportion cannot be estimated for the entire year is considered. The effect of these missing segments on the variance of the at-harvest stratum crop proportion estimator is considered when missing segments are not replaced, and when missing segments are replaced by segments not sampled in previous years. The principle recommendations are to replace missing segments according to some specified strategy, and to use a sequential procedure for selecting a sampling design; i.e., choose an optimal two year design and then, based on the observed two year design after segment losses have been taken into account, choose the best possible three year design having the observed two year parent design

    Incorporating partially identified sample segments into acreage estimation procedures: Estimates using only observations from the current year

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    Several methods of estimating individual crop acreages using a mixture of completely identified and partially identified (generic) segments from a single growing year are derived and discussed. A small Monte Carlo study of eight estimators is presented. The relative empirical behavior of these estimators is discussed as are the effects of segment sample size and amount of partial identification. The principle recommendations are (1) to not exclude, but rather incorporate partially identified sample segments into the estimation procedure, (2) try to avoid having a large percentage (say 80%) of only partially identified segments, in the sample, and (3) use the maximum likelihood estimator although the weighted least squares estimator and least squares ratio estimator both perform almost as well. Sets of spring small grains (North Dakota) data were used

    Area estimation using multiyear designs and partial crop identification

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    Statistical procedures were developed for large area assessments using both satellite and conventional data. Crop acreages, other ground cover indices, and measures of change were the principal characteristics of interest. These characteristics are capable of being estimated from samples collected possibly from several sources at varying times, with different levels of identification. Multiyear analysis techniques were extended to include partially identified samples; the best current year sampling design corresponding to a given sampling history was determined; weights reflecting the precision or confidence in each observation were identified and utilized, and the variation in estimates incorporating partially identified samples were quantified

    Duality in Least Squares Theory

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    Survivability of intelligent transportation systems.

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    Federal Highway Administration, Washington, D.C.Virginia Department of Transportation, Richmond.Mode of access: Internet.Author corporate affiliation: Virginia Transportation Research Council, Charlottesville.Subject code: FSSubject code: SDBSubject code: WW*IJSubject code: X
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