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Rating Crop Insurance Policies with Efficient Nonparametric Estimators that Admit Mixed Data Types AgEcon
Racine, Jeffrey S.; Ker, Alan P..
The identification of improved methods for characterizing crop yield densities has experienced a recent surge in activity due in part to the central role played by crop insurance in the Agricultural Risk Protection Act of 2000 (estimates of yield densities are required for the determination of insurance premium rates). Nonparametric kernel methods have been successfully used to model yield densities; however, traditional kernel methods do not handle the presence of categorical data in a satisfactory manner and have therefore tended to be applied on a county-by-county basis. By utilizing recently developed kernel methods that admit mixed data types, we are able to model the yield density jointly across counties, leading to substantial finite sample...
Tipo: Journal Article Palavras-chave: Discrete data; Insurance rating; Kernel estimation; Yield distributions; Risk and Uncertainty.
Ano: 2006 URL: http://purl.umn.edu/10146
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Speaking Stata: Graphing distributions AgEcon
Cox, Nicholas J..
Graphing univariate distributions is central to both statistical graphics, in general, and Stata’s graphics, in particular. Now that Stata 8 is out, a review of official and user-written commands is timely. The emphasis here is on going beyond what is obviously and readily available, with pointers to minor and major trickery and various user-written commands. For plotting histogram-like displays, kernel-density estimates and plots based on distribution functions or quantile functions, a large variety of choices is now available to the researcher.
Tipo: Journal Article Palavras-chave: Graphics; Histogram; Spikeplot; Dotplot; Onewayplot; Kdensity; Distplot; Qplot; Skewplot; Bin width; Rug; Density function; Kernel estimation; Transformations; Logarithmic scale; Root scale; Intensity function; Distribution function; Quantile function; Skewness; Research Methods/ Statistical Methods.
Ano: 2004 URL: http://purl.umn.edu/116213
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