CoxCurveSolver
solves the confidence interval for a cox model, starting at the optimum point and
iteratively optimizing end-points of intervals. Intervals updated using the bisection method.
CoxCurveSolver(
df,
time1 = "%trunc%",
time2 = "%trunc%",
event0 = "event",
names = c("CONST"),
term_n = c(0),
tform = "loglin",
keep_constant = c(0),
a_n = c(0),
modelform = "M",
control = list(),
strat_col = "null",
cens_weight = "null",
model_control = list(),
cons_mat = as.matrix(c(0)),
cons_vec = c(0)
)
returns a list of the final results
a data.table containing the columns of interest
column used for time period starts
column used for time period end
column used for event status
columns for elements of the model, used to identify data columns
term numbers for each element of the model
list of string function identifiers, used for linear/step
binary values to denote which parameters to change
list of initial parameter values, used to determine the number of parameters. May be either a list of vectors or a single vector.
string specifying the model type: M, ME, A, PA, PAE, GMIX, GMIX-R, GMIX-E
list of parameters controlling the convergence, see Def_Control() for options or vignette("Control_Options")
column to stratify by if needed
column containing the row weights
controls which alternative model options are used, see Def_model_control() for options and vignette("Control_Options") for further details
Matrix containing coefficients for a system of linear constraints, formatted as matrix
Vector containing constants for a system of linear constraints, formatted as vector
Other Cox Wrapper Functions:
RunCaseControlRegression_Omnibus()
,
RunCoxNull()
,
RunCoxRegression()
,
RunCoxRegression_Basic()
,
RunCoxRegression_CR()
,
RunCoxRegression_Guesses_CPP()
,
RunCoxRegression_Omnibus()
,
RunCoxRegression_Omnibus_Multidose()
,
RunCoxRegression_Single()
,
RunCoxRegression_Strata()
,
RunCoxRegression_Tier_Guesses()