|Controls printed output (
||Specifies what to do when the measurements are not all made at the same locations (
||Pointer to store the variograms, cross-variograms and associated information for use in
||Maximum lag in all directions|
||Length of the step or steps in which lag is incremented|
||Directions along which to form the variogram, scalar for a single direction in 2 dimensions, variate for several directions in 2 dimensions, and pairs of variates for 3 dimensional data|
||Angle subtended by each segment along the
||Coordinate system used for the geometry for discretizing the lag (
||Diameter at which the segments over which averaging is to be done should cease to expand; default
||Minimum number of points required at a particular lag point for the cross-variogram to be estimated there; default 1|
||Mean function (
||Measurements as a variate|
||Locations of each set of measurements in the first dimension|
||Locations of each set of measurements in the second dimension (if recorded in more than 1 dimension)|
||Locations of each set of measurements in the third dimension (if recorded in 3 dimensions)|
FCOVARIOGRAM directive forms a covariogram structure containing auto- and cross-variograms for pairs from a list of variates.
The data are supplied as a list of variates using the
DATA parameter, where each variate contains the measurements for each variable. The locations of the measurements are supplied using parameters
X2 (for two or three dimensions) and
X3 (for three dimensions) parameters.
METHOD option specifies how to calculate the cross-variograms. The setting
commonpoints specifies that only those points observed in common in every sample are to be included; the method described in Section 8.3.4 of Part 2 of the Guide to the Genstat Command Language are then used. Alternatively, the setting
allnocrossnugget can be used when the sampling locations do not match. This uses an algorithm outlined in Künsch, Papritz & Bassi (1997) that performs least-squares fitting of the cloud of products of differences to estimate the expected value of these products. If there are no common points, the nugget variance cannot be calculated. However, if there is partial sampling (i.e. some common points), the setting
allwithcrossnugget can be used to shift the cross-variograms by the semivariance at the origin to estimate the nugget effect.
The maximum lag distance in all directions to which the variograms are calculated is set by the
MAXLAG option. The increments in distance are set by the
STEPLENGTH option, where you can supply a scalar to define equally-spaced steps or a variate to specify the steps themselves. The directions along which to form the variograms are supplied in degrees using the
DIRECTIONS option. The geometry used for the directions is given by the
COORDSYSTEM option: the setting
mathematical specifies directions counter-clockwise from east, and
geographical specifies clockwise from north (for the first direction only in three dimensions). Each direction is at the centre of an angular range. The angle is the same in every direction, and is defined by the
SEGMENTS option. For a single direction in two dimensions the
DIRECTIONS option should be set to a scalar, while for several directions it should be set to a variate. For directions in three dimensions,
DIRECTIONS should specify a pair of variates. The
MAXCONEDIATMETER option can be used to specify a diameter at which the segments cease to expand. For cross-variograms that are formed using all points the minimum number of points required at each lag can be specified using the
DRIFT option can be used to calculate the variograms after removing a systematic component. Setting the
DRIFT option to linear or quadratic will fit a regression to the observations and then form the variograms on the residuals.
COVARIOGRAM option allows you to specify pointer to save the auto-variograms, cross-variograms and associated information. Its elements contain:
1 a matrix with columns of variograms and cross-variograms and rows indexed by lags within directions;
2 a variate of counts at the lags in each direction;
3 distances of the lags in each direction;
4 horizontal angles;
5 vertical angles;
7 distance classes;
9 pointer containing identifiers of the
10 number of dimensions.
This structure provides the information required to fit models to the covariogram using the directive
variograms displays each of the auto- and cross-variograms, while the setting
autovariogram displays only the auto-variograms.
Restrictions are ignored.
Künsch, H.R., Papritz, A. & Bassi, F. (1997) Generalized cross-covariances and their estimation. Mathematical Geology, 29, 779-799.
Commands for: Spatial statistics.
" Examples 2:8.3.6, 2:8.3.7, 2:8.3.8 & 2:8.3.9 " " Data are measurements of concentrations of trace metals in the topsoil of the Swiss Jura. Data analyzed are Cadmium, Nickel and Zinc taken from Goovaerts prediction subset. See Goovaerts (1997) Geostatistics for Natural Resources Evaluation." FILEREAD [PRINT=summary; NAME=\ '%GENDIR%/Examples/GuidePart2/Goovaerts.dat']X1,X2,Cd,Ni,Zn FCOVARIOGRAM [PRINT=statistics; MAXLAG=2.1; STEP=0.1; DIRECTIONS=0;\ SEGMENTS=180; MAXCONE=500; MINCOUNT=1;\ COVARIOGRAM=Save_cov] DATA=Cd,Ni,Zn; X1=X1; X2=X2 " Plot the variograms and covariograms." GETATTRIBUTE [ATTRIBUTE=columns] Save_cov['semivar']; Lab FRAME 11...16; YLOWER=2(0.66,0.33,0); YUPPER=2(0.98,0.65,0.32);\ XLOWER=(0,0.5)3; XUPPER=(0.5,1)3 TEXT scr; VALUE='clear' PEN 1; SYMBOL='circle' XAXIS 11...16; TITLE='Lag distance/km'; LOWER=0; LROTATION=45 YAXIS 11...16; TITLE='Semi-variance'; LOWER=0 FOR [INDEX=i; NTIMES=6] DGRAPH [WINDOW=i+10; KEY=0; TITLE=Lab['columns']$[i]; SCREEN=#scr]\ Save_cov['semivar']$[*;i]; Save_cov['distances']$[*;i] TEXT scr; VALUE='keep' ENDFOR " Model the coregionalization." MCOVARIOGRAM [PRINT=summary,estimates; WEIGHTING=counts;\ MAXLAG=3; MINCOUNT=20; COVARIOGRAM=Save_cov]\ MODELTYPE=nugget,spherical,spherical; INITIAL=*,0.2,1.3;\ ESTIMATES=Save_est DCOVARIOGRAM [ESTIMATES=Save_est] Save_cov " Read the locations of the prediction points." MATRIX [ROWS=1547; COLUMNS=2] Mpoints OPEN '%GENDIR%/Examples/GuidePart2/Mpoints.dat'; CHANNEL=2 READ [CHANNEL=2] Mpoints CLOSE 2; FILETYPE=input " Produce predictions and variances for target variable Cadmium." COKRIGE [PRINT=description; Y=Cd; POINTS=Mpoints; RADII=20;\ SEARCHNEIGHBOURHOOD=local] Cd; X1=X1; X2=X2;\ ESTIMATES=Save_est; PREDICTIONS=Predictions;\ VARIANCES=Variances " Plot the predictions and variances." VARIATE [NVALUES=NROWS(Mpoints)] Xpos,Ypos EQUATE T(Mpoints); !p(Xpos,Ypos) GROUPS [REDEFINE=yes] Xpos,Ypos; FACTOR=Xfac,Yfac; LEVELS=Xlevs,Ylevs TABULATE [CLASSIFICATION=Yfac,Xfac] Predictions,Variances;\ MEANS=Zvals,Zvars MATRIX [ROWS=!(#Ylevs); COLUMNS=!(#Xlevs)] Mpredictions; !(#Zvals) MATRIX [ROWS=!(#Ylevs); COLUMNS=!(#Xlevs)] Mvariances; !(#Zvars) XAXIS [RESET=yes] 1 YAXIS [RESET=yes] 1 PEN 2,3; COLOUR='azure','midnightblue' DSHADE [TITLE='Cokriged estimates for cadmium in the Swiss Jura';\ YORIENTATION=normal; GRIDMETHOD=*] Mpredictions; PEN=!(2,3)\ DSHADE [TITLE='Cokriging variances for cadmium in the Swiss Jura';\ YORIENTATION=normal; GRIDMETHOD=*] Mvariances; PEN=!(2,3) PEN [RESET=yes] 1,2,3