Methods for working with mrgsims objects

Source: R/mrgsims.R

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)

Arguments

x

mrgsims object
name

name of column of simulated output to retain
...

passed to other functions
row.names

passed to as.data.frame
optional

passed to as.data.frame
object

passed to show

Details

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

  • as.tbl coerces simulated to tbl_df; requires dplyr

  • summary coerces simulated data to data.frame and passes to summary.data.frame

  • plot plots simulated data; see plot_mrgsims

See also

stime

Examples


## 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")
}