linfit [ parameter=value ... ] [ inputfile ... ]
Parameters are: x_var, y_vars, printout
The function linfit determines the linear relationship between pairs of variables, e.g. y = slope * x + bias. x_var is a single variable representing x in the above relationship, and y_vars can be specified to be one or more sets of y values. Both the x and y variables specified must be in the same TeraScan dataset and must have the same type and dimensions.
NOTE: the algorithm assumes that errors exist in both the x and y variables and therefore minimizes the distance perpindicular from each point to the regression line (see REFERENCES).
For each x-y pair, linfit outputs the following information:
Mean Mean values of x, y, slope and bias Stand Dev Standard deviations of x, y, slope and bias Correlation Correlation between x and y Count Number of data points in the y variables Good Number of good points in common between x and y
Specifies the x variable.
There is no default.
Specifies the y variables to use in determining the linear relationship against x. A linear relation and its corresponding output is produced for each y variable specified. If the list is preceded by a minus sign, then all variables, except those listed, are included. Wildcards * and ? are allowed. If the y_var list happens to include the x variable, this variable is filtered out by the processing and no corresponding output is printed for this x,y (i.e. x,x) pair.
The default is to include all variables.
Whether or not to send the printout to the standard printer. Valid responses are [yes, no].
The default is no.
This example uses a dataset with four variables representing temperature and specific humidity at the sea surface and low-level atmosphere. These variables are denoted: Ts, Qs, Ta, Qa. The linear regression is computed for Qs, Qa, Ta against Ts.
% linfit bndlayer.tdf x_var : char( 31) ? Ts y_vars : char(255) ? [] printout : char( 3) ? [no] Linear Fit Page 1 bndlayer.tdf Ts Qa Bias Slope Mean 20.2394 12.1777 -0.050745 0.604188 Stand. Dev. 8.07105 5.04592 2.18954 0.00342603 Correlation 0.927116 Good 5082 Count 16200 bndlayer.tdf Ts Qs Bias Slope Mean 20.2733 16.2691 0.258171 0.789754 Stand. Dev. 8.03644 6.38559 1.67935 0.00259728 Correlation 0.973736 Good 5055 Count 16200 bndlayer.tdf Ts Ta Bias Slope Mean 20.1032 19.17 -1.77989 1.04211 Stand. Dev. 8.16278 8.50055 1.79828 0.00269242 Correlation 0.982929 Good 5249 Count 16200
spectral, dimcorr, binavg, xcorrel, polyfit, correlate, regress, stats.
York, D., 1966: Least-Squares Fitting of a Straight Line. Canadian Journal of Physics, Vol. 44, 1079-1086. Kermack, K. A. and J. B. S. Haldane, 1950: Biometrika, Vol. 37, 30.
Last Update: $Date: 1998/05/29 18:33:03 $