RcppDynProg (version 0.2.1)

solve_for_partition: Solve for a piecewise linear partiton.

Description

Solve for a good set of right-exclusive x-cuts such that the overall graph of y~x is well-approximated by a piecewise linear function. Solution is a ready for use with with base::findInterval() and stats::approx() (demonstrated in the examples).

Usage

solve_for_partition(
  x,
  y,
  ...,
  w = NULL,
  penalty = 0,
  min_n_to_chunk = 1000,
  min_seg = 1,
  max_k = length(x)
)

Value

a data frame appropriate for stats::approx().

Arguments

x

numeric, input variable (no NAs).

y

numeric, result variable (no NAs, same length as x).

...

not used, force later arguments by name.

w

numeric, weights (no NAs, positive, same length as x).

penalty

per-segment cost penalty.

min_n_to_chunk

minimum n to subdivied problem.

min_seg

positive integer, minimum segment size.

max_k

maximum segments to divide into.

Examples

# example data
d <- data.frame(
  x = 1:8,
  y = c(1, 2, 3, 4, 4, 3, 2, 1))

# solve for break points
soln <- solve_for_partition(d$x, d$y)
# show solution
print(soln)

# label each point 
d$group <- base::findInterval(
  d$x,
  soln$x[soln$what=='left'])
# apply piecewise approximation
d$estimate <- stats::approx(
  soln$x,
  soln$pred,
  xout = d$x,
  method = 'linear',
  rule = 2)$y
# show result
print(d)