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### V6 Resource File                             ###
### generated on: Mon May 16 10:05:08 EDT 2011   ###
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### This file is designed to be delivered to the ###
### translator. 					###
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662=Calculating Kriging coefficients;
738=RuntimeEnv is not set, Kriging technique object is not properly configured
4827=Gaussian
7431=Filter Distance:
7716=Unexpected EOF while reading inputs matrix in coefficients data file {0}
8689=Could not calculate recommended number of designs
16198=Set the maximum number of optimization iterations used to find the best fit.
24099=Insufficient number of sampling points for Kriging initialization: {0}
27246=Fit type decides whether to treat individual inputs differently or not.
29088=Points that are closer that this value are filtered before fitting.
32229=Matern Cubic
33799=Could not store Kriging configuration in plug-in
37129=Kriging configuration problem, \ncoefficients data file copy was not created, \ninitialization aborted
37161=Could not calculate min number of designs
40177=Isotropic fit treats all inputs equally; anisotropic treats them differently.
40619=Could not evaluate Kriging approximation
48376=Unexpected EOF while reading outputs matrix in coefficients data file {0}
49125=Set the distance for filtering points that are \'too\' close.
50326=Kriging initialization cancelled
50955=Failed to read Kriging coefficient file
52324=Failed to initialize Kriging approximation
56427=Kriging Technique Options
60782=Exponential
62087=Coefficients data file {0} does not contain the following approximation parms: {1}
62099=Approximation is not configured, no output parameters
63924=Could not get Kriging configuration from plugin
64910=Kriging initialization failed
68773=Could not choose next sample point
70636=Failed to restore Kriging approximation from internal data
72526=Approximation is not configured, no input parameters
74453=Could not get approx property in Kriging
76997=Anisotropic
77883=Four correlations are available: Gaussian, exponential, Matern linear and cubic
78208=Fit Type:
80849=Choose the auto-correlation function for the fit.
82299=Maximum Iterations to Fit:
85084=Isotropic
85346=Could not reset coeff data in approx properties
86086=Fitting Kriging model for response \'y {0} \'
90405=Correlation Function:
91523=The optimization algorithm will iterate as many times as apecified here
92548=Matern Linear
98878=Reading Kriging coefficients from coefficients data file
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###   Meta Model I18N string                       #
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desc=Kriging approximation technique plugin
dispname=Kriging Model
techniqueoptionsdesc=<b>Fit Type:</b> <ul><li>Anisotropic fit is the general case for ordinary Kriging when every independent variable behaves differently. </li><li>Isotropic fit is faster than the Anisotropic fit but assumes that all independent variables behave similarly. </li> </ul><b>Correlation Function:</b> <ul><li>Gaussian - Typically used for approximating smooth functions; however, produces a poor fit when sampling points are too close. </li><li>Exponential - If the sample points are close, use the Exponential correlation function.</li> <li>Matern Linear - Use the Matern Linear correlation function if the Gaussian and Matern Cubic correlation functions produced an unacceptable fit.</li> <li>Matern Cubic - Typically, Matern Cubic correlation function is more accurate than the Matern Linear. </li> </ul><b>Filter Distance: </b> Used to filter points from the sample based on distance to avoid a poor fit. <br><b>Maximum Iterations to Fit: </b> Limits the maximum number of optimization iterations used to fit a model for each response based on this value.
longdesc=Kriging approximation is a type of interpolation technique. Kriging approximations are extremely flexible due to the wide range of correlation functions which can be chosen for building the meta model. Furthermore, depending on the choice of the correlation function, the meta model can either "honor the data," providing an exact interpolation of the data, or "smooth the data," providing an inexact interpolation. <p> The Isight implementation of Kriging models allows the use of the common correlation functions such as Exponential, Gaussian, Matern Linear and Matern Cubic. <p> Initialization of the Kriging approximation requires at least 2n+1 design points, where n is the number of inputs.  The component being approximated can be executed multiple times to collect the required data.  Alternatively, a data file can serve as the initialization source.
