fame (version 1.13)

linearSplineIntegration: Linear Spline Integration

Description

lintegrate gives the values resulting from integrating a linear spline, while ilspline returns linear splines that integrate to given values.

Usage

lintegrate(x, y, xint, stepfun = F, rule = 0)
ilspline(xint, w)

Arguments

x

x coordinates of the linear spline F defined by (x, y)

y

y coordinates of the linear spline F defined by (x, y)

xint

x intervals, i.e. [x[1], x[2]] is the first interval, [x[2], x[3]] is the second interval, and so on.

stepfun

if TRUE, F is a left-continuous step function. The default (FALSE) says F is continuous.

rule

one of {0, 1, NA} to specify the behavior of F outside the range of x. Use zero if F is zero outside the range of x, NA if F is NA outside the range of x, and one if F is to be linearly extende

w

values the linear spline must integrate to

Value

• lintegrate returns a vector of length length(xint) - 1.

  ilspline returns a list with components named 'x' and 'y'.

Details

lintegrate integrates the linear spline F defined by (x,y) over the xint intervals. The value of F outside the range of x is specified by the rule argument: rule == 0 --> F(z) = 0 for z outside the range of x rule == NA --> F(z) = NA for z outside the range of x rule == 1 --> F(z) extended for z outside the range of x

If stepfun is TRUE, F(z) is assumed to be a left-continuous step function and the last value of y is never accessed.

(x[i], y[i]) pairs with NA values in either x[i] or y[i] NA are ignored in constructing F.

ilspline finds linear splines that integrate over the N intervals specified by the monotonically increasing N+1 vector xint to the N values given in w. The function finds N-vectors x and y such that:

(i) x[j] = (xint[j-1] + xint[j])/2, i.e., the values of x are the midpoints of the intervals specified by xint, and

(ii) the linear spline that passes through the (x[i], y[i]) pairs (and is extended to xint[1] and xint[N+1] by linear extrapolation) integrates over each interval [xint[j],xint[j+1]] to w[j]. In fact, w can actually be an M by N matrix, in which case the y found by the function is also an M by N matrix, with each column of y giving the y coordinates of a linear spline that integrates to the corresponding column of w.

References

~put references to the literature/web site here ~

See Also

spline, approx

Examples

w <- 10 + cumsum(rnorm(10))
blah <- ilspline(1:11, w)
ww <- lintegrate(blah$x, blah$y, 1:11, rule = 1)
w - ww  ## should be all zeroes (or very close to zero)