About control_stats.log
Each row of control_stats.log results from the execution of a single run. The output statistics contained in this file are referred to as scores for each run. The coefficient columns at the end of each row are the corresponding initializing coefficient values. The composite score gives a best result across all statistics. By scanning across the line you can see which statistics fit better than others within a single execution, and which coefficient values performed the best. The scores in control_stats.log may be linked by row to the avg.log, std_dev.log and coeff.log files by the run number.

Contents of control_stats.log:

run: a run consists of a single set of coefficient values and is executed MONTE_CARLO_ITERATIONS number of times from start to stop year

product: all other scores multiplied together

compare: modeled population for final year / actual population for final year, or
IF P_{modeled >} P_actual { 1 - (modeled population for final year / actual population for final year)}.

pop: least squares regression score for modeled urbanization compared to actual urbanization for the control years

edges: least squares regression score for modeled urban edge count compared to actual urban edge count for the control years

clusters: least squares regression score for modeled urban clustering compared to known urban clustering for the control years

cluster_size: least squares regression score for modeled average urban cluster size compared to known average urban cluster size for the control years

leesalee: a shape index, a measurement of spatial fit between the model's growth and the known urban extent for the control years

slope: least squares regression of average slope for modeled urbanized cells compared to average slope of known urban cells for the control years

%urban: least squares regression of percent of available pixels urbanized compared to the urbanized pixels for the control years

xmean: least squares regression of average x_values for modeled urbanized cells compared to average x_values of known urban cells for the control years

ymean: least squares regression of average y_values for modeled urbanized cells compared to average y_values of known urban cells for the control years

rad: least squares regression of average radius of the circle which encloses the urban pixels

Fmatch: a proportion of goodness of fit across landuse classes. { #_modeled_LU correct / ( #_modeled_LU correct +  #_modeled_LU wrong)}

diff: run initializing dispersion_coefficient value

brd: run initializing breed_coefficient value

sprd: run initializing spread_coefficient value

slp: run initializing slope_coefficient value

RG: run initializing road_gravity_coefficient value