# NOT RUN {
## Not run. When executing, the following takes about 2 minutes running time.
## Summary of regular cjamp function
#set.seed(10)
#genodata <- generate_genodata(n_SNV = 20, n_ind = 100)
#phenodata <- generate_phenodata_2_copula(genodata = genodata$SNV1,
# MAF_cutoff = 1, prop_causal = 1,
# tau = 0.2, b1 = 0.3, b2 = 0.3)
#predictors <- data.frame(X1 = phenodata$X1, X2 = phenodata$X2,
# genodata[, 1:3])
#results <- cjamp(Y1 = phenodata$Y1, Y2 = phenodata$Y2,
# predictors_Y1 = predictors, predictors_Y2 = predictors,
# copula = "2param", optim_method = "BFGS", trace = 0,
# kkt2tol = 1E-16, SE_est = TRUE, pval_est = TRUE,
# n_iter_max = 10)
#summary(results)
#
## Summary of looped cjamp function
#covariates <- data.frame(X1 = phenodata$X1, X2 = phenodata$X2)
#predictors <- genodata
#results <- cjamp_loop(Y1 = phenodata$Y1, Y2 = phenodata$Y2,
# covariates_Y1 = covariates,
# covariates_Y2 = covariates,
# predictors = predictors, copula = "Clayton",
# optim_method = "BFGS", trace = 0, kkt2tol = 1E-16,
# SE_est = TRUE, pval_est = TRUE, n_iter_max = 10)
#summary(results)
# }
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