Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Life Sciences
Optimum Design For Exponential Model Using An Exponential Loss Function And Its Applications In Agriculture, Imad H. Khamis
Optimum Design For Exponential Model Using An Exponential Loss Function And Its Applications In Agriculture, Imad H. Khamis
Conference on Applied Statistics in Agriculture
Accelerated life testing has been used for years in engineering. Test units are run at high stress and fail sooner than at design stress. The lifetime at design stress is estimated by extrapolation using a regression model. This paper considers the optimum design of accelerated life tests in which two levels of stresses, high and low are constantly applied. For the exponential model the expected value of an exponential loss function of the arameter is to be used. The initial sample proportion allocated to the high stress which minimizes the expected loss function is determined. In the agriculture context, plants …
An Introduction To Generalized Linear Mixed Models, Charles E. Mcculloch
An Introduction To Generalized Linear Mixed Models, Charles E. Mcculloch
Conference on Applied Statistics in Agriculture
The generalized linear mixed model (GLMM) generalizes the standard linear model in three ways: accommodation of non-normally distributed responses, specification of a possibly non-linear link between the mean of the response and the predictors, and allowance for some forms of correlation in the data. As such, GLMMs have broad utility and are of great practical importance. Two special cases of the GLMM are the linear mixed model (LMM) and the generalized linear model (GLM). Despite the utility of such models, their use has been limited due to the lack of reliable, well-tested estimation and testing methods. I first describe and …
Analysis Of The Spatial Distribution Of Sugarbeet Plants, Stephen D. Kachman, John A. Smith
Analysis Of The Spatial Distribution Of Sugarbeet Plants, Stephen D. Kachman, John A. Smith
Conference on Applied Statistics in Agriculture
The spatial distribution of emerged sugarbeet plants is an important aspect of the performance of sugarbeet planters. Three major components influencing the spatial distribution are the ability to drop a single seed at a time, the ability to drop the seeds a fixed distance apart, and the ability of the seed to emerge. A model has been developed to describe the distribution of the spacing between emerged sugarbeet plants. The model consists of a mixture of normal and gamma distributions. The spatial data consists of the distance between neighboring emerged plants. Spatial data was collected on 7 planters operated at …