| .microsimulationLdFlags {microsimulation} | R Documentation |
Internal function
Description
Is this function needed? We could define the current stream in open code.
Again, is this needed?
Usage
.microsimulationLdFlags()
inlineCxxPlugin(...)
LdFlags()
microsimulation.init(PACKAGE = "microsimulation")
microsimulation.exit(PACKAGE = "microsimulation")
unsigned(seed)
signed(seed)
rnormPos(n, mean = 0, sd = 1, lbound = 0)
set.user.Random.seed(seed, PACKAGE = "microsimulation")
advance.substream(seed, n, PACKAGE = "microsimulation")
next.user.Random.substream(PACKAGE = "microsimulation")
user.Random.seed(PACKAGE = "microsimulation")
enum(obj, labels, start = 0)
enum(obj) <- value
RNGstate()
frontier(x, y, concave = TRUE, convex = NULL)
lines_frontier(x, y, pch = 19, type = "b", ...)
discountedPoint(y, time, dr)
ICER(object1, object2, ...)
.onLoad(lib, pkg)
.onUnload(libpath)
Arguments
... |
other arguments |
PACKAGE |
package for the seed |
seed |
random number seed |
n |
number of sub-streams to advance |
mean |
numeric for the mean of the (untruncated) normal distribution (default=0) |
sd |
numeric for the sd of the (untruncated) normal distribution (default=1) |
lbound |
numeric for the lower bound (default=0) |
obj |
integer or logical for factor levels |
labels |
labels for the factor levels |
start |
first value of the levels |
value |
labels for the factor levels |
x |
vector of x coordinates |
y |
the undiscounted value |
concave |
logical for whether to calculate a concave frontier (default=TRUE) |
convex |
logical for whether to calculate a convex frontier (default=NULL) |
pch |
type of pch for the plotted symbols (default=19) |
type |
join type (default="b") |
time |
the time of the event |
dr |
discount rate, expressed as a percentage |
object1 |
first object |
object2 |
second object |
lib |
library string |
pkg |
package string |
libpath |
library path string |
Value
No return value, called for side effects
No return value, called for side effects
No return value, called for side effects
unsigned seed
signed seed
numeric vector
invisibly returns the new seed
the advanced seed
invisibly returns TRUE – called for side effect
random seed
the new factor
update the factor
a list with oldseed (the old value of .Random.seed), and reset(), which resets .Random.seed
a list with components x and y for the frontier
No return value, called for side effects
numeric vector