#Data file containing:
#Y = observed case count in each area (750m grid cell)
#pop = population in each area (750m grid cell) (divided by 100, to give population units as '100 children')
#NO2 = average annual NO2 concentration in each area (750m grid cell) - measured in mg m-3 above the
# baseline concentration for the study region of approximately 20mg m-3
#ker = 605 x 96 dimension matrix of kernel weights k[i, j] where j indexes latent grid cells and i indexes areas
# in the study region. There are 96 latent grid cell chosen for this analysis, each of dimension approx
# 2.8km x 3.0km, which cover the entire study region (defined to have south-west corner at co-ordinate at
# (399000,402000) metres, and north-east corner at co-ordinate(428250,422250) meters) plus a 2km buffer
# zone surrounding the study region. The distance scale of the Gaussian kernel has been fixed at 1km.
# This kernel matrix was generated using the Splus / R function create.kernel
#prec = scaling factor for kernel weights (kernel weights to be used in calculations = ker / prec)
#I, J = number of areas in study region (605) and number of latent grid cells (96)
#area = area (in squared km) of each latent grid cell (needed for specifying priors)
list(ker = structure(.Data = c(0.0001, 0.0001, 0.503325, 1461.495861, 4916.432528, 72.683263, 0.000349, 0.0001, 0.0001, 0.0001, 0.269442,
782.372273, 2631.879155, 38.909019, 0.000187, 0.0001, 0.0001, 0.0001, 0.000602, 1.746658, 5.875709,
0.086865, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.018913,
430.962047, 5614.657197, 405.460865, 0.016305, 0.0001, 0.0001, 0.0001, 0.010125, 230.703873, 3005.654843,
217.052506, 0.008728, 0.0001, 0.0001, 0.0001, 0.0001, 0.51505, 6.710169, 0.484573, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 4.392524, 1799.197305, 1799.197305,
4.392524, 0.0001, 0.0001, 0.0001, 0.0001, 7.678452, 3145.128203, 3145.128203, 7.678452, 0.0001, 0.0001,
0.0001, 0.0001, 0.095366, 39.062485, 39.062485, 0.095366, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.000532,
0.000532, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.281437, 817.204139, 2749.052609, 40.641281, 0.000195, 0.0001,
0.0001, 0.0001, 0.491973, 1428.532478, 4805.544601, 71.043925, 0.000341, 0.0001, 0.0001, 0.0001, 0.00611,
17.74237, 59.684853, 0.882365, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.000241, 0.000812, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.010575, 240.975002, 3139.469102, 226.715864, 0.009117, 0.0001, 0.0001, 0.0001, 0.018487,
421.241891, 5488.021126, 396.315877, 0.015937, 0.0001, 0.0001, 0.0001, 0.00023, 5.231823, 68.161209,
4.922242, 0.000198, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.000928, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.000231, 44.095638, 2779.143604, 783.692071, 0.248117, 0.0001, 0.0001, 0.0001, 0.000405, 77.082393,
4858.145856, 1369.950938, 0.433726, 0.0001, 0.0001, 0.0001, 0.0001, 0.957363, 60.33816, 17.014787, 0.005387,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.000821, 0.000232, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.003405, 84.665145, 1172.408508,
89.990101, 0.003949, 0.0001, 0.0001, 0.0001, 0.02066, 513.777313, 7114.579324, 546.090983, 0.023966, 0.0001,
0.0001, 0.0001, 0.001208, 30.033989, 415.898465, 31.922956, 0.001401, 0.0001, 0.0001, 0.0001, 0.0001,
0.00286, 0.039605, 0.00304, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 15.177147, 1026.61073, 305.178058, 0.1051, 0.0001,
0.0001, 0.0001, 0.000442, 92.100163, 6229.828106, 1851.925749, 0.637786, 0.0001, 0.0001, 0.0001, 0.0001,
5.383919, 364.178376, 108.258414, 0.037283, 0.0001, 0.0001, 0.0001, 0.0001, 0.000513, 0.03468, 0.010309,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001, 0.0001,
0.0001, 0.0001, 0.0001, 0.0001
OpenBUGS.zip_Gibbs bayesian_Gibbs采样_bayesian bugs_garch openbugs
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OpenBUGS.zip_Gibbs bayesian_Gibbs采样_bayesian bugs_garch openbugs （2000个子文件） 
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