src/test/scripts/functions/builtin/cox.dml

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num_records = $n;
lambda = $l;
p_event = $p;
# parameters related to the cox model
num_features = $m;
sparsity = $sp;
p_censor = 1 - p_event; # prob. that record is censored
n_seed = $sd;

v = $v;
# generate feature matrix
X_t = rand (rows = num_records, cols = num_features, min = 1, max = 5, pdf = "uniform", sparsity = sparsity, seed = n_seed);
# generate coefficients
B = rand (rows = num_features, cols = 1, min = -1.0, max = 1.0, pdf = "uniform", sparsity = 1.0, seed = n_seed);

# generate timestamps
U = rand (rows = num_records, cols = 1, min = 0.000000001, max = 1, seed = n_seed);
T_1 = (-log (U) / (lambda * exp (X_t %*% B)) ) ^ (1/v);

Y = matrix (0, rows = num_records, cols = 2);
event = floor (rand (rows = num_records, cols = 1, min = (1 - p_censor), max = (1 + p_event), seed = n_seed));
n_time = sum (event);
Y[,2] = event;

# binning of event times
min_T = min (T_1);
max_T = max (T_1);
# T_1 = T_1 - min_T;
len = max_T - min_T;
num_bins = len / n_time;
T_1 = ceil (T_1 / num_bins);

# print ("min(T) " + min(T) + " max(T) " + max(T));
Y[,1] = T_1;

X = cbind (Y, X_t);

TE = matrix ("1 2", rows = 2, cols = 1);
F = seq (1, num_features);
R = matrix (0, rows = 1, cols = 1);

[M, S, T, COV, RT, XO] = cox(X, TE, F, R, $alpha, $tol, $moi, $mii);

write(M, $M);
write(S, $S);
write(T, $T);
write(COV, $COV);
write(RT, $RT);
write(XO, $XO);