`tpmatrix()`

both defines and evaluates a transition probability matrix in which
elements are expressions. It can be used within `define_tparams()`

to
create a transition probability matrix or directly to create a `tparams_transprobs()`

object. These are, in turn, ultimately used to create a CohortDtstmTrans object
for simulating health state transitions.

tpmatrix(...)

... | Named values of expressions defining elements of the matrix. Each
element of |
---|

Returns a `tpmatrix`

object that inherits from `data.table`

where each column is an element of the transition probability matrix with
elements ordered rowwise.

A `tpmatrix`

is a 2-dimensional tabular object that stores flattened
square transition probability matrices in each row. Each transition probability
matrix is filled rowwise. The complementary probability
(equal to \(1\) minus the sum of the probabilities
of all other elements in a row of a transition probability matrix)
can be conveniently referred to as `C`

. There can
only be one complement for each row in a transition
probability matrix.

#> s1_s1 s1_s2 s2_s1 s2_s2 #> 1: 0.3 0.7 0 1 #> 2: 0.4 0.6 0 1tpmatrix( C, p_12, C, 1 )#> s1_s1 s1_s2 s2_s1 s2_s2 #> 1: 0.3 0.7 0 1 #> 2: 0.4 0.6 0 1#> s1_s1 s1_s2 s2_s1 s2_s2 #> 1: 0.5 0.5 0.3 0.7# Pass vectors and data frames p1 <- data.frame( p_12 = c(.7, .6), p_13 = c(.1, .2) ) p2 <- data.frame( p_21 = 0, p_22 = c(.4, .45), p_23 = c(.6, .55) ) p3 <- data.frame( p_31 = c(0, 0), p_32 = c(0, 0), p_33 = c(1, 1) ) tpmatrix( C, p1, p2, p3 )#> s1_s1 s1_s2 s1_s3 s2_s1 s2_s2 s2_s3 s3_s1 s3_s2 s3_s3 #> 1: 0.2 0.7 0.1 0 0.40 0.60 0 0 1 #> 2: 0.2 0.6 0.2 0 0.45 0.55 0 0 1