These methods help the user view simulation output and extract
simulated data to work with further. The methods listed here
for the most part have generics defined by R or other R packages.
See the seealso
section for other methods defined
by mrgsolve
that have their own documentation pages.
# S4 method for mrgsims
$(x, name)
# S4 method for mrgsims
tail(x, ...)
# S4 method for mrgsims
head(x, ...)
# S4 method for mrgsims
dim(x)
# S4 method for mrgsims
names(x)
# S4 method for mrgsims
as.data.frame(x, row.names = NULL, optional = FALSE, ...)
# S4 method for mrgsims
as.matrix(x, ...)
# S3 method for mrgsims
summary(object, ...)
# S4 method for mrgsims
show(object)
mrgsims object
name of column of simulated output to retain
passed to other functions
passed to as.data.frame
passed to as.data.frame
passed to show
Most methods should behave as expected according to other method commonly used in R (e.g. head, tail, as.data.frame, etc ...)
$
selects a column in the simulated data and
returns numeric
head
see head.matrix
; returns
simulated data
tail
see tail.matrix
; returns
simulated data
dim
, nrow
, ncol
returns dimensions,
number of rows, and number of columns in simulated data
as.data.frame
coerces simulated data to data.frame
and returns the data.frame
as.matrix
returns matrix of simulated data
summary
coerces simulated data to data.frame
and passes to summary.data.frame
plot
plots simulated data; see plot_mrgsims
## example("mrgsims")
mod <- mrgsolve::house() %>% init(GUT=100)
out <- mrgsim(mod)
class(out)
#> [1] "mrgsims"
#> attr(,"package")
#> [1] "mrgsolve"
if (FALSE) {
out
}
head(out)
#> ID time GUT CENT RESP DV CP
#> 1 1 0.00 100.00000 0.00000 50.00000 0.000000 0.000000
#> 2 1 0.25 74.08182 25.74883 48.68223 1.287441 1.287441
#> 3 1 0.50 54.88116 44.50417 46.18005 2.225208 2.225208
#> 4 1 0.75 40.65697 58.08258 43.61333 2.904129 2.904129
#> 5 1 1.00 30.11942 67.82976 41.37943 3.391488 3.391488
#> 6 1 1.25 22.31302 74.74256 39.57649 3.737128 3.737128
tail(out)
#> ID time GUT CENT RESP DV CP
#> 476 1 118.75 9.202240e-44 0.2753340 49.92950 0.01376670 0.01376670
#> 477 1 119.00 5.342789e-44 0.2719137 49.93038 0.01359569 0.01359569
#> 478 1 119.25 2.453278e-44 0.2685360 49.93124 0.01342680 0.01342680
#> 479 1 119.50 2.498865e-44 0.2652002 49.93209 0.01326001 0.01326001
#> 480 1 119.75 1.869677e-44 0.2619058 49.93293 0.01309529 0.01309529
#> 481 1 120.00 1.163038e-44 0.2586523 49.93377 0.01293262 0.01293262
dim(out)
#> [1] 481 7
names(out)
#> [1] "ID" "time" "GUT" "CENT" "RESP" "DV" "CP"
mat <- as.matrix(out)
df <- as.data.frame(out)
if (FALSE) {
out$CP
}
plot(out)
if (FALSE) {
plot(out, CP~.)
plot(out, CP+RESP~time, scales="same", xlab="Time", main="Model sims")
}