lab2 - DATASETS NEEDED: coalash.dt (Coal Ash dataset)

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Sheet1 Page 1 DATASETS NEEDED: coalash.dt (Coal Ash dataset) www4.stat.ncsu.edu/~fuentes/coalash.dat davis.dat (topographic heights) www4.stat.ncsu.edu/~fuentes/davis.dat ozone.dat (ozone values) www4.stat.ncsu.edu/~fuentes/ozone.dat software R with library geoR, fields and akima PART II Spatial prediction: ##EXERCISE 1: Estimating covariance parameters ##EXERCISE 2: Moving neighborhood kriging ##EXERCISE 3: ANISTROPY ##EXERCISE 4: Maps and Images ####################################################################### # download your data using read.table # to learn more about read.table type # > ? read.table coal.ash<-read.table('coalash.dat') coal.m<-as.matrix(coal.ash) davis.dat<-read.table('davis.dat') davis.m<-as.matrix(davis.dat) ################################### ##EXERCISE 1: Estimating model parameters ###A. Bayesian estimates of model parameters: #Function: krige.bayes
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Sheet1 Page 2 # You obtain posteriors for the trend, range, partial sill and nugget # Recommended (default) priors: # uniform for beta, 1/sigma^2 for the partial sill # and discrete uniform for the range and nugget. # # aniso.pars are the parameters for anisotropy: stretching and rotation angle. # # the default is with nugget 0, but you # can also get a posterior for the nugget when you give a prior to the nugget, # by saying nugget.prior="uniform" # #Additional information: #---------------------- # This function computes (Bayesian) estimates of a spatial linear #model and performs Bayesian and/or kriging prediction in a set of #locations specified by the user. # Priors options for mean and/or covariance parameters # coords : data coordinates (vector for 1d or matrix for 2d data) # data : vector with data values # locations : coordinates of points to be estimated (vector for 1d or # matrix for 2d data). If locations='no' only model parameters estimates are #returned if the full bayesian model is considered. # trend.d : trend data in data locations. Default is constant trend. #The options '1st' or '2nd' builts a first or second degree polinomial. # trend.l : trend data in locations to be estimated. Default #is constant trend. The options '1st' or '2nd' builts a first or second #degree polinomial. # #Example:
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This note was uploaded on 08/01/2008 for the course ST 790M taught by Professor Fuentes during the Fall '07 term at N.C. State.

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lab2 - DATASETS NEEDED: coalash.dt (Coal Ash dataset)

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