stick.ar.0: Broken-Stick Regression for Independent Data

Description Usage Arguments Details Value Note Author(s) References See Also Examples

View source: R/code.r

Description

This function is the main engine for bentcable.ar when a broken stick (i.e. γ=0 for bent cable) model is assumed for independent data. For AR(p) time-series data, this function is intended for determining an appropriate p and initial values for the stick parameters.

Usage

1
stick.ar.0(init.vect, y.vect, t.vect = NULL, n = NA)

Arguments

init.vect

A numeric vector of initial values, in the form of c(b0,b1,b2,tau).

y.vect

A numeric vector of response data.

t.vect

A numeric vector of design points, which need not be equidistant. Specifying t.vect=NULL is equivalent to specifying the default time points c(0,1,2,...).

n

Length of response vector (optional).

Details

The returned object is compatible with a cable.ar.p.iter object for independent data.

The broken stick as a special case of the bent cable has form f(t) = b_0 + b_1 t + b_2 (t-τ) I\{t>τ\} .

Broken-stick regression by maximum likelihood for independent data is performed via nonlinear least-squares estimation of θ=(b_0,b_1,b_2,τ) through the built-in R function nls. The estimation relies on the user-supplied initial values in init.

Value

fit

An nls object that is the maximum likelihood fit.

y, t, n

As supplied by the user.

p, stick

The values 0 and TRUE, respectively; used internally by bentcable.ar and cable.ar.0.fit.

Note

This function is intended for internal use by bentcable.ar.

Author(s)

Grace Chiu

References

See the bentcableAR package references.

See Also

cable.ar.p.iter, fullcable.t, cable.fit.known.change.

Examples

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2
3
data(sockeye)

stick.ar.0( c(13,.1,-.7,12), sockeye$logReturns )

Example output

Trying 'nls()' Gauss-Newton algorithm...
12.1804 :  13.0  0.1 -0.7 12.0
8.916925 :  13.24087877  0.02560975 -0.50014863 11.57224783
8.854351 :  13.25855520  0.02078893 -0.52236006 11.80691892
8.854106 :  13.25855526  0.02078892 -0.52236005 11.79694061
Converged!
$fit
Nonlinear regression model
  model: y.vect ~ fullcable.t(t.vect, b0, b1, b2, tau, 0)
   data: parent.frame()
      b0       b1       b2      tau 
13.25856  0.02079 -0.52236 11.79694 
 residual sum-of-squares: 8.854

Number of iterations to convergence: 3 
Achieved convergence tolerance: 1.409e-07

$y
 [1] 12.655625 13.655085 13.667217 13.417511 12.499414 13.437136 13.966513
 [8] 13.732741 13.682008 12.992086 13.618007 13.151390 13.654253 12.884477
[15] 11.789193 11.671612 11.082143 12.528156 10.858999  8.188689  9.903488

$t
 [1]  0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20

$n
[1] 21

$p
[1] 0

$stick
[1] TRUE

bentcableAR documentation built on May 2, 2019, 11:01 a.m.