3,992 research outputs found
The effects of estimation of censoring, truncation, transformation and partial data vectors
The purpose of this research was to attack statistical problems concerning the estimation of distributions for purposes of predicting and measuring assembly performance as it appears in biological and physical situations. Various statistical procedures were proposed to attack problems of this sort, that is, to produce the statistical distributions of the outcomes of biological and physical situations which, employ characteristics measured on constituent parts. The techniques are described
Confidence regions for variance ratios in variance components models
Statistical mechanics for constructing confidence intervals for variance ratios in balanced and unbalanced experimental design
Archeological Survey of the South Tyger Watershed
At the request of the Soil Conservation Service an archeological survey was conducted by the Institute of Archeology and Anthropology, University of South Carolina on three proposed reservoir projects in the South Tyger River Watershed, Greenville County, South Carolina. The survey took place in February 1975 and revealed eight previously unrecorded sites in the watershed area. None of these sites are of a significance to warrant further extensive investigation, and there is little possibility that the reservoir projects will destroy any significant archeological sites.https://scholarcommons.sc.edu/archanth_books/1058/thumbnail.jp
Postcard: 1st Annual Chrysanthemum Show, Nov. 9, \u2707. Pres. Guild, Argonia, Kansas
This black and white photographic postcard features rows of Chrysanthemums in vases. Three rows of vases are on shelves covered with cloth. There is written text on the bottom of the card. Handwriting is on the back of the card.https://scholars.fhsu.edu/tj_postcards/1519/thumbnail.jp
The Ashley River: A Survey of Seventeenth Century Sites
https://scholarcommons.sc.edu/archanth_books/1183/thumbnail.jp
Stochastic compartmental analysis - Some applications and examples of estimation in a pulse labelled system
Stochastic compartmental analysis with examples of estimation in pulse labelled syste
Autocalibration with the Minimum Number of Cameras with Known Pixel Shape
In 3D reconstruction, the recovery of the calibration parameters of the
cameras is paramount since it provides metric information about the observed
scene, e.g., measures of angles and ratios of distances. Autocalibration
enables the estimation of the camera parameters without using a calibration
device, but by enforcing simple constraints on the camera parameters. In the
absence of information about the internal camera parameters such as the focal
length and the principal point, the knowledge of the camera pixel shape is
usually the only available constraint. Given a projective reconstruction of a
rigid scene, we address the problem of the autocalibration of a minimal set of
cameras with known pixel shape and otherwise arbitrarily varying intrinsic and
extrinsic parameters. We propose an algorithm that only requires 5 cameras (the
theoretical minimum), thus halving the number of cameras required by previous
algorithms based on the same constraint. To this purpose, we introduce as our
basic geometric tool the six-line conic variety (SLCV), consisting in the set
of planes intersecting six given lines of 3D space in points of a conic. We
show that the set of solutions of the Euclidean upgrading problem for three
cameras with known pixel shape can be parameterized in a computationally
efficient way. This parameterization is then used to solve autocalibration from
five or more cameras, reducing the three-dimensional search space to a
two-dimensional one. We provide experiments with real images showing the good
performance of the technique.Comment: 19 pages, 14 figures, 7 tables, J. Math. Imaging Vi
The Grove and Flagg Plantations Survey
https://scholarcommons.sc.edu/archanth_books/1061/thumbnail.jp
A computer program for the mixed analysis of variance model based on maximum likelihood
Computer program for mixed analysis of variance model based on maximum likelihoo
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