tests/test_modelSim.R
In mathildesautreuil/survMS: Survival Model Simulation
library(survMS)
### Survival data simulated from Cox model
res_paramW = get_param_weib(med = 2228, mu = 2325)
listCoxSim_n500_p1000 <- modelSim(model = "cox", matDistr = "unif", matParam = c(-1,1), n = 500,
p = 1000, pnonull = 20, betaDistr = 1, hazDistr = "weibull",
hazParams = c(res_paramW$a, res_paramW$lambda), seed = 1, d = 0)
print(listCoxSim_n500_p1000)
hist(listCoxSim_n500_p1000)
plot(listCoxSim_n500_p1000, ind = sample(1:500, 5))
plot(listCoxSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
df_p1000_n500 = data.frame(time = listCoxSim_n500_p1000$TC,
event = listCoxSim_n500_p1000$delta,
listCoxSim_n500_p1000$Z)
df_p1000_n500[1:6,1:10]
dim(df_p1000_n500)
### Survival data simulated from AFT model
res_paramLN = get_param_ln(var = 200000, mu = 1134)
listAFTSim_n500_p1000 <- modelSim(model = "AFT", matDistr = "unif", matParam = c(-1,1), n = 500,
p = 100, pnonull = 100, betaDistr = 1, hazDistr = "log-normal",
hazParams = c(res_paramLN$a, res_paramLN$lambda),
Phi = 0, seed = 1, d = 0)
hist(listAFTSim_n500_p1000)
plot(listAFTSim_n500_p1000, ind = sample(1:500, 5))
plot(listAFTSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
df_p1000_n500 = data.frame(time = listAFTSim_n500_p1000$TC,
event = listAFTSim_n500_p1000$delta,
listAFTSim_n500_p1000$Z)
df_p1000_n500[1:6,1:10]
dim(df_p1000_n500)
### Survival data simulated from AH model
res_paramLN = get_param_ln(var=170000, mu=2325)
listAHSim_n500_p1000 <- modelSim(model = "AH", matDistr = "unif", matParam = c(-1,1), n = 500,
p = 100, pnonull = 100, betaDistr = 1.5, hazDistr = "log-normal",
hazParams = c(res_paramLN$a*4, res_paramLN$lambda),
Phi = 0, seed = 1, d = 0)
print(listAHSim_n500_p1000)
hist(listAHSim_n500_p1000)
plot(listAHSim_n500_p1000, ind = sample(1:500, 5))
plot(listAHSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
### Correlated survival data simulated from Cox model
res_paramW = get_param_weib(med = 2.5, mu = 1.2)
listCoxSimCor_n500_p1000 <- modelSim(model = "cox", matDistr = "mvnorm", matParam = c(0,0.6), n = 500,
p = 1000, pnonull = 10, betaDistr = 1, hazDistr = "weibull",
hazParams = c(res_paramW$a, res_paramW$lambda), seed = 1, d = 0)
print(listCoxSimCor_n500_p1000)
hist(listCoxSimCor_n500_p1000)
Heatmap(listCoxSimCor_n500_p1000, ind = 1:15, k = 3)
# draw(listCoxSimCor_n500_p1000)
# ### Survival data simulated from Cox model
# res_paramW = get_param_weib(med = 1062, mu = 1134)
# listCoxSim_n500_p1000 <- modelSim(model = "cox", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 1000, pnonull = 20, betaDistr = 1, hazDistr = "weibull",
# hazParams = c(1.5, 1), seed = 1, d = 0)
# print(listCoxSim_n500_p1000)
# hist(listCoxSim_n500_p1000)
# plot(listCoxSim_n500_p1000, ind = sample(1:500, 5))
# plot(listCoxSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
# df_p1000_n500 = data.frame(time = listCoxSim_n500_p1000$TC,
# event = listCoxSim_n500_p1000$delta,
# listCoxSim_n500_p1000$Z)
# df_p1000_n500[1:6,1:10]
# dim(df_p1000_n500)
#
# ## COX/LN model
# listCoxSim_n500_p1000 <- modelSim(model = "cox", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 100, pnonull = 20, betaDistr = 1, hazDistr = "log-normal",
# hazParams = c(0.25,1), seed = 1)#c(res_paramLN$a*3, res_paramLN$lambda), seed = 1, d = 0)
# print(listCoxSim_n500_p1000)
# hist(listCoxSim_n500_p1000)
# plot(listCoxSim_n500_p1000, ind = sample(1:500, 5))
# plot(listCoxSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
#
# ## COX/exponetial model
# res_paramE = get_param_exp(med = 1062, mu = 1134)
# listCoxSim_n500_p1000 <- modelSim(model = "cox", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 1000, pnonull = 20, betaDistr = 1, hazDistr = "exponential",
# hazParams = res_paramE$lambda, seed = 1, d = 0)
# print(listCoxSim_n500_p1000)
# hist(listCoxSim_n500_p1000)
# plot(listCoxSim_n500_p1000, ind = sample(1:500, 5))
#
# df_p1000_n500 = data.frame(time = listCoxSim_n500_p1000$TC,
# event = listCoxSim_n500_p1000$delta,
# listCoxSim_n500_p1000$Z)
# df_p1000_n500[1:6,1:10]
# dim(df_p1000_n500)
#
# listCoxSim_n500_p25000 <- modelSim(model = "cox", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 25000, pnonull = 20, betaDistr = 1, hazDistr = "weibull",
# hazParams = c(3, 4), seed = 1, d = 0)
# print(listCoxSim_n500_p25000)
# hist(listCoxSim_n500_p25000)
# plot(listCoxSim_n500_p25000, ind = sample(1:500, 5))
# plot(listCoxSim_n500_p25000, ind = sample(1:500, 5), type = "hazard")
#
# df_p25m_n500 = data.frame(time = listCoxSim_n500_p25000$TC,
# event = listCoxSim_n500_p25000$delta,
# listCoxSim_n500_p25000$Z)
# df_p25m_n500[1:6,1:10]
#
# ### Survival data simulated from AFT model
# res_paramLN = get_param_ln(var = 200000, mu = 1134)
# listAFTSim_n500_p1000 <- modelSim(model = "AFT", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 1000, pnonull = 20, betaDistr = 1, hazDistr = "log-normal",
# hazParams = c(0.25, 0.5), Phi = 0, seed = 1, d = 0)
# print(listAFTSim_n500_p1000)
# hist(listAFTSim_n500_p1000)
# plot(listAFTSim_n500_p1000, ind = sample(1:500, 10), type = "surv")
# plot(listAFTSim_n500_p1000, ind = sample(1:500, 10), type = "hazard")
# df_p1000_n500 = data.frame(time = listAFTSim_n500_p1000$TC,
# event = listAFTSim_n500_p1000$delta,
# listAFTSim_n500_p1000$Z)
# df_p1000_n500[1:6,1:10]
# dim(df_p1000_n500)
# res_paramW = get_param_weib(med = 1062, mu = 1134)
# listAFTSim_n500_p1000 <- modelSim(model = "AFT", matDistr = "unif", matParam = c(0,1), n = 500,
# p = 1000, pnonull = 20, betaDistr = 1, hazDistr = "weibull",
# hazParams = c(1.5, 1),
# Phi = 0, seed = 1, d = 0)
# print(listAFTSim_n500_p1000)
# hist(listAFTSim_n500_p1000)
# plot(listAFTSim_n500_p1000, ind = sample(1:500, 5))
# plot(listAFTSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
# df_p1000_n500 = data.frame(time = listAFTSim_n500_p1000$TC,
# event = listAFTSim_n500_p1000$delta,
# listAFTSim_n500_p1000$Z)
# df_p1000_n500[1:6,1:10]
# dim(df_p1000_n500)
#
# ### Survival data simulated from Shifted AFT model
# res_paramLN = get_param_ln(var=170000, mu=2325)
# listAFTSim_n500_p1000 <- modelSim(model = "AFTshift", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 100, pnonull = 100, betaDistr = "unif", hazDistr = "log-normal",
# hazParams = c(0.3, res_paramLN$lambda),
# Phi = 0, seed = 100, d = 0)
# print(listAFTSim_n500_p1000)
# hist(listAFTSim_n500_p1000)
# plot(listAFTSim_n500_p1000, ind = sample(1:500, 10), type = "surv")
# plot(listAFTSim_n500_p1000, ind = sample(1:500, 10), type = "hazard")
# df_p1000_n500 = data.frame(time = listAFTSim_n500_p1000$TC,
# event = listAFTSim_n500_p1000$delta,
# listAFTSim_n500_p1000$Z)
# df_p1000_n500[1:6,1:10]
# dim(df_p1000_n500)
#
# res_paramW = get_param_weib(med = 1062, mu = 1134)
# listAFTSim_n500_p1000 <- modelSim(model = "AFTshift", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 1000, pnonull = 20, betaDistr = "unif", hazDistr = "weibull",
# hazParams = c(res_paramW$a, res_paramW$lambda),
# Phi = 0, seed = 1, d = 0)
# print(listAFTSim_n500_p1000)
# hist(listAFTSim_n500_p1000)
# plot(listAFTSim_n500_p1000, ind = sample(1:500, 5))
# plot(listAFTSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
# df_p1000_n500 = data.frame(time = listAFTSim_n500_p1000$TC,
# event = listAFTSim_n500_p1000$delta,
# listAFTSim_n500_p1000$Z)
# df_p1000_n500[1:6,1:10]
# dim(df_p1000_n500)
#
# # write.csv(df_p1000_n500, file = paste0(path, "DF_RegScreen_n500_p1000.csv"), row.names = F)
# # listAFTSim_n500_p25000 <- AFTSim(matDistr = "unif", matParam = c(-1,1), n = 500, p = 25000,
# # pnonull = 20, betaDistr = 1, hazDistr = "weibull",
# # hazParams = c(res_paramLN$a, res_paramLN$lambda),
# # seed = 1, d = 0)
# # hist(listAFTSim_n500_p25000$TC)
# # df_p25m_n500 = data.frame(time = listAFTSim_n500_p25000$TC,
# # event = listAFTSim_n500_p25000$delta,
# # listAFTSim_n500_p25000$Z)
# # df_p25m_n500[1:6,1:10]
#
# ### Survival data simulated from Shifted AH model
# res_paramW = get_param_weib(med = 1062, mu = 1134)
# listAHSim_n500_p1000 <- modelSim(model = "AH", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 1000, pnonull = 20, betaDistr = 1, hazDistr = "weibull",
# hazParams = c(res_paramW$a, res_paramW$lambda),
# Phi = 0, seed = 1, d = 0)
# print(listAHSim_n500_p1000)
# hist(listAHSim_n500_p1000)
# plot(listAHSim_n500_p1000, ind = sample(1:500, 5))
# plot(listAHSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
# df_p1000_n500 = data.frame(time = listAHSim_n500_p1000$TC,
# event = listAHSim_n500_p1000$delta,
# listAHSim_n500_p1000$Z)
# df_p1000_n500[1:6,1:10]
# dim(df_p1000_n500)
#
# res_paramLN = get_param_ln2(med = 2280, mu = 2325)
# res_paramLN = get_param_ln(var=170000, mu=2325)
# listAHSim_n500_p1000 <- modelSim(model = "AH", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 10, pnonull = 10, betaDistr = 1, hazDistr = "log-normal",
# hazParams = c(res_paramLN$a*3, res_paramLN$lambda),
# Phi = 0, seed = 1, d = 0)
# print(listAHSim_n500_p1000)
# hist(listAHSim_n500_p1000)
# plot(listAHSim_n500_p1000, ind = sample(1:500, 5))
# plot(listAHSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
# ## test
#
# # write.csv(df_p1000_n500, file = paste0(path, "DF_RegScreen_n500_p1000.csv"), row.names = F)
# system.time(listAFTSim_n500_p25000 <- modelSim(model = "AFT", matDistr = "unif", matParam = c(-1,1),
# n = 500, p = 25000, pnonull = 20, betaDistr = 1,
# hazDistr = "weibull",
# hazParams = c(res_paramLN$a, res_paramLN$lambda),
# seed = 1, d = 0))
# hist(listAFTSim_n500_p25000)
# df_p25m_n500 = data.frame(time = listAFTSim_n500_p25000$TC,
# event = listAFTSim_n500_p25000$delta,
# listAFTSim_n500_p25000$Z)
# df_p25m_n500[1:6,1:10]
#
#
# system.time(listCoxSim_n500_p25000 <- modelSim(model = "cox", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 25000, pnonull = 20, betaDistr = 1, hazDistr = "weibull",
# hazParams = c(res_paramW$a, res_paramW$lambda), seed = 1, d = 0))
# print(listCoxSim_n500_p25000)
# hist(listCoxSim_n500_p25000)
# plot(listCoxSim_n500_p25000, ind = sample(1:500, 5))
#
# df_p25m_n500 = data.frame(time = listCoxSim_n500_p25000$TC,
# event = listCoxSim_n500_p25000$delta,
# listCoxSim_n500_p25000$Z)
# df_p25m_n500[1:6,1:10]
#
# ### Survival data simulated from AFT model
# res_paramLN = get_param_ln(var = 200000, mu = 1134)
# system.time(listAFTSim_n500_p1000 <- modelSim(model = "AFT", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 100, pnonull = 100, betaDistr = 1, hazDistr = "log-normal",
# hazParams = c(res_paramLN$a, res_paramLN$lambda),
# Phi = 0, seed = 1, d = 0))
# hist(listAFTSim_n500_p1000)
# df_p1000_n500 = data.frame(time = listAFTSim_n500_p1000$TC,
# event = listAFTSim_n500_p1000$delta,
# listAFTSim_n500_p1000$Z)
# df_p1000_n500[1:6,1:10]
# dim(df_p1000_n500)
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library(survMS)
### Survival data simulated from Cox model
res_paramW = get_param_weib(med = 2228, mu = 2325)
listCoxSim_n500_p1000 <- modelSim(model = "cox", matDistr = "unif", matParam = c(-1,1), n = 500,
p = 1000, pnonull = 20, betaDistr = 1, hazDistr = "weibull",
hazParams = c(res_paramW$a, res_paramW$lambda), seed = 1, d = 0)
print(listCoxSim_n500_p1000)
hist(listCoxSim_n500_p1000)
plot(listCoxSim_n500_p1000, ind = sample(1:500, 5))
plot(listCoxSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
df_p1000_n500 = data.frame(time = listCoxSim_n500_p1000$TC,
event = listCoxSim_n500_p1000$delta,
listCoxSim_n500_p1000$Z)
df_p1000_n500[1:6,1:10]
dim(df_p1000_n500)
### Survival data simulated from AFT model
res_paramLN = get_param_ln(var = 200000, mu = 1134)
listAFTSim_n500_p1000 <- modelSim(model = "AFT", matDistr = "unif", matParam = c(-1,1), n = 500,
p = 100, pnonull = 100, betaDistr = 1, hazDistr = "log-normal",
hazParams = c(res_paramLN$a, res_paramLN$lambda),
Phi = 0, seed = 1, d = 0)
hist(listAFTSim_n500_p1000)
plot(listAFTSim_n500_p1000, ind = sample(1:500, 5))
plot(listAFTSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
df_p1000_n500 = data.frame(time = listAFTSim_n500_p1000$TC,
event = listAFTSim_n500_p1000$delta,
listAFTSim_n500_p1000$Z)
df_p1000_n500[1:6,1:10]
dim(df_p1000_n500)
### Survival data simulated from AH model
res_paramLN = get_param_ln(var=170000, mu=2325)
listAHSim_n500_p1000 <- modelSim(model = "AH", matDistr = "unif", matParam = c(-1,1), n = 500,
p = 100, pnonull = 100, betaDistr = 1.5, hazDistr = "log-normal",
hazParams = c(res_paramLN$a*4, res_paramLN$lambda),
Phi = 0, seed = 1, d = 0)
print(listAHSim_n500_p1000)
hist(listAHSim_n500_p1000)
plot(listAHSim_n500_p1000, ind = sample(1:500, 5))
plot(listAHSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
### Correlated survival data simulated from Cox model
res_paramW = get_param_weib(med = 2.5, mu = 1.2)
listCoxSimCor_n500_p1000 <- modelSim(model = "cox", matDistr = "mvnorm", matParam = c(0,0.6), n = 500,
p = 1000, pnonull = 10, betaDistr = 1, hazDistr = "weibull",
hazParams = c(res_paramW$a, res_paramW$lambda), seed = 1, d = 0)
print(listCoxSimCor_n500_p1000)
hist(listCoxSimCor_n500_p1000)
Heatmap(listCoxSimCor_n500_p1000, ind = 1:15, k = 3)
# draw(listCoxSimCor_n500_p1000)
# ### Survival data simulated from Cox model
# res_paramW = get_param_weib(med = 1062, mu = 1134)
# listCoxSim_n500_p1000 <- modelSim(model = "cox", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 1000, pnonull = 20, betaDistr = 1, hazDistr = "weibull",
# hazParams = c(1.5, 1), seed = 1, d = 0)
# print(listCoxSim_n500_p1000)
# hist(listCoxSim_n500_p1000)
# plot(listCoxSim_n500_p1000, ind = sample(1:500, 5))
# plot(listCoxSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
# df_p1000_n500 = data.frame(time = listCoxSim_n500_p1000$TC,
# event = listCoxSim_n500_p1000$delta,
# listCoxSim_n500_p1000$Z)
# df_p1000_n500[1:6,1:10]
# dim(df_p1000_n500)
#
# ## COX/LN model
# listCoxSim_n500_p1000 <- modelSim(model = "cox", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 100, pnonull = 20, betaDistr = 1, hazDistr = "log-normal",
# hazParams = c(0.25,1), seed = 1)#c(res_paramLN$a*3, res_paramLN$lambda), seed = 1, d = 0)
# print(listCoxSim_n500_p1000)
# hist(listCoxSim_n500_p1000)
# plot(listCoxSim_n500_p1000, ind = sample(1:500, 5))
# plot(listCoxSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
#
# ## COX/exponetial model
# res_paramE = get_param_exp(med = 1062, mu = 1134)
# listCoxSim_n500_p1000 <- modelSim(model = "cox", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 1000, pnonull = 20, betaDistr = 1, hazDistr = "exponential",
# hazParams = res_paramE$lambda, seed = 1, d = 0)
# print(listCoxSim_n500_p1000)
# hist(listCoxSim_n500_p1000)
# plot(listCoxSim_n500_p1000, ind = sample(1:500, 5))
#
# df_p1000_n500 = data.frame(time = listCoxSim_n500_p1000$TC,
# event = listCoxSim_n500_p1000$delta,
# listCoxSim_n500_p1000$Z)
# df_p1000_n500[1:6,1:10]
# dim(df_p1000_n500)
#
# listCoxSim_n500_p25000 <- modelSim(model = "cox", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 25000, pnonull = 20, betaDistr = 1, hazDistr = "weibull",
# hazParams = c(3, 4), seed = 1, d = 0)
# print(listCoxSim_n500_p25000)
# hist(listCoxSim_n500_p25000)
# plot(listCoxSim_n500_p25000, ind = sample(1:500, 5))
# plot(listCoxSim_n500_p25000, ind = sample(1:500, 5), type = "hazard")
#
# df_p25m_n500 = data.frame(time = listCoxSim_n500_p25000$TC,
# event = listCoxSim_n500_p25000$delta,
# listCoxSim_n500_p25000$Z)
# df_p25m_n500[1:6,1:10]
#
# ### Survival data simulated from AFT model
# res_paramLN = get_param_ln(var = 200000, mu = 1134)
# listAFTSim_n500_p1000 <- modelSim(model = "AFT", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 1000, pnonull = 20, betaDistr = 1, hazDistr = "log-normal",
# hazParams = c(0.25, 0.5), Phi = 0, seed = 1, d = 0)
# print(listAFTSim_n500_p1000)
# hist(listAFTSim_n500_p1000)
# plot(listAFTSim_n500_p1000, ind = sample(1:500, 10), type = "surv")
# plot(listAFTSim_n500_p1000, ind = sample(1:500, 10), type = "hazard")
# df_p1000_n500 = data.frame(time = listAFTSim_n500_p1000$TC,
# event = listAFTSim_n500_p1000$delta,
# listAFTSim_n500_p1000$Z)
# df_p1000_n500[1:6,1:10]
# dim(df_p1000_n500)
# res_paramW = get_param_weib(med = 1062, mu = 1134)
# listAFTSim_n500_p1000 <- modelSim(model = "AFT", matDistr = "unif", matParam = c(0,1), n = 500,
# p = 1000, pnonull = 20, betaDistr = 1, hazDistr = "weibull",
# hazParams = c(1.5, 1),
# Phi = 0, seed = 1, d = 0)
# print(listAFTSim_n500_p1000)
# hist(listAFTSim_n500_p1000)
# plot(listAFTSim_n500_p1000, ind = sample(1:500, 5))
# plot(listAFTSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
# df_p1000_n500 = data.frame(time = listAFTSim_n500_p1000$TC,
# event = listAFTSim_n500_p1000$delta,
# listAFTSim_n500_p1000$Z)
# df_p1000_n500[1:6,1:10]
# dim(df_p1000_n500)
#
# ### Survival data simulated from Shifted AFT model
# res_paramLN = get_param_ln(var=170000, mu=2325)
# listAFTSim_n500_p1000 <- modelSim(model = "AFTshift", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 100, pnonull = 100, betaDistr = "unif", hazDistr = "log-normal",
# hazParams = c(0.3, res_paramLN$lambda),
# Phi = 0, seed = 100, d = 0)
# print(listAFTSim_n500_p1000)
# hist(listAFTSim_n500_p1000)
# plot(listAFTSim_n500_p1000, ind = sample(1:500, 10), type = "surv")
# plot(listAFTSim_n500_p1000, ind = sample(1:500, 10), type = "hazard")
# df_p1000_n500 = data.frame(time = listAFTSim_n500_p1000$TC,
# event = listAFTSim_n500_p1000$delta,
# listAFTSim_n500_p1000$Z)
# df_p1000_n500[1:6,1:10]
# dim(df_p1000_n500)
#
# res_paramW = get_param_weib(med = 1062, mu = 1134)
# listAFTSim_n500_p1000 <- modelSim(model = "AFTshift", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 1000, pnonull = 20, betaDistr = "unif", hazDistr = "weibull",
# hazParams = c(res_paramW$a, res_paramW$lambda),
# Phi = 0, seed = 1, d = 0)
# print(listAFTSim_n500_p1000)
# hist(listAFTSim_n500_p1000)
# plot(listAFTSim_n500_p1000, ind = sample(1:500, 5))
# plot(listAFTSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
# df_p1000_n500 = data.frame(time = listAFTSim_n500_p1000$TC,
# event = listAFTSim_n500_p1000$delta,
# listAFTSim_n500_p1000$Z)
# df_p1000_n500[1:6,1:10]
# dim(df_p1000_n500)
#
# # write.csv(df_p1000_n500, file = paste0(path, "DF_RegScreen_n500_p1000.csv"), row.names = F)
# # listAFTSim_n500_p25000 <- AFTSim(matDistr = "unif", matParam = c(-1,1), n = 500, p = 25000,
# # pnonull = 20, betaDistr = 1, hazDistr = "weibull",
# # hazParams = c(res_paramLN$a, res_paramLN$lambda),
# # seed = 1, d = 0)
# # hist(listAFTSim_n500_p25000$TC)
# # df_p25m_n500 = data.frame(time = listAFTSim_n500_p25000$TC,
# # event = listAFTSim_n500_p25000$delta,
# # listAFTSim_n500_p25000$Z)
# # df_p25m_n500[1:6,1:10]
#
# ### Survival data simulated from Shifted AH model
# res_paramW = get_param_weib(med = 1062, mu = 1134)
# listAHSim_n500_p1000 <- modelSim(model = "AH", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 1000, pnonull = 20, betaDistr = 1, hazDistr = "weibull",
# hazParams = c(res_paramW$a, res_paramW$lambda),
# Phi = 0, seed = 1, d = 0)
# print(listAHSim_n500_p1000)
# hist(listAHSim_n500_p1000)
# plot(listAHSim_n500_p1000, ind = sample(1:500, 5))
# plot(listAHSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
# df_p1000_n500 = data.frame(time = listAHSim_n500_p1000$TC,
# event = listAHSim_n500_p1000$delta,
# listAHSim_n500_p1000$Z)
# df_p1000_n500[1:6,1:10]
# dim(df_p1000_n500)
#
# res_paramLN = get_param_ln2(med = 2280, mu = 2325)
# res_paramLN = get_param_ln(var=170000, mu=2325)
# listAHSim_n500_p1000 <- modelSim(model = "AH", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 10, pnonull = 10, betaDistr = 1, hazDistr = "log-normal",
# hazParams = c(res_paramLN$a*3, res_paramLN$lambda),
# Phi = 0, seed = 1, d = 0)
# print(listAHSim_n500_p1000)
# hist(listAHSim_n500_p1000)
# plot(listAHSim_n500_p1000, ind = sample(1:500, 5))
# plot(listAHSim_n500_p1000, ind = sample(1:500, 5), type = "hazard")
# ## test
#
# # write.csv(df_p1000_n500, file = paste0(path, "DF_RegScreen_n500_p1000.csv"), row.names = F)
# system.time(listAFTSim_n500_p25000 <- modelSim(model = "AFT", matDistr = "unif", matParam = c(-1,1),
# n = 500, p = 25000, pnonull = 20, betaDistr = 1,
# hazDistr = "weibull",
# hazParams = c(res_paramLN$a, res_paramLN$lambda),
# seed = 1, d = 0))
# hist(listAFTSim_n500_p25000)
# df_p25m_n500 = data.frame(time = listAFTSim_n500_p25000$TC,
# event = listAFTSim_n500_p25000$delta,
# listAFTSim_n500_p25000$Z)
# df_p25m_n500[1:6,1:10]
#
#
# system.time(listCoxSim_n500_p25000 <- modelSim(model = "cox", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 25000, pnonull = 20, betaDistr = 1, hazDistr = "weibull",
# hazParams = c(res_paramW$a, res_paramW$lambda), seed = 1, d = 0))
# print(listCoxSim_n500_p25000)
# hist(listCoxSim_n500_p25000)
# plot(listCoxSim_n500_p25000, ind = sample(1:500, 5))
#
# df_p25m_n500 = data.frame(time = listCoxSim_n500_p25000$TC,
# event = listCoxSim_n500_p25000$delta,
# listCoxSim_n500_p25000$Z)
# df_p25m_n500[1:6,1:10]
#
# ### Survival data simulated from AFT model
# res_paramLN = get_param_ln(var = 200000, mu = 1134)
# system.time(listAFTSim_n500_p1000 <- modelSim(model = "AFT", matDistr = "unif", matParam = c(-1,1), n = 500,
# p = 100, pnonull = 100, betaDistr = 1, hazDistr = "log-normal",
# hazParams = c(res_paramLN$a, res_paramLN$lambda),
# Phi = 0, seed = 1, d = 0))
# hist(listAFTSim_n500_p1000)
# df_p1000_n500 = data.frame(time = listAFTSim_n500_p1000$TC,
# event = listAFTSim_n500_p1000$delta,
# listAFTSim_n500_p1000$Z)
# df_p1000_n500[1:6,1:10]
# dim(df_p1000_n500)
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