shapeparams: Shape Parameters

Description

Given the output from the shape function (including the chosen shape, chosen information criteria value ic, vector of fitted values thetab, and corresponding $\bold{x}$, e.g., years), this routine calculates a set of parameters that describe the behavior of the fitted trajectory.

Usage

shapeparams(shapenum, ic, thetab, x)

Arguments

shapenum

A number with the index $1$ to $7$.

A $k$ by $N$ matrix where the $i$th column is the vector of "BIC" or "CIC" values used to choose the best shape for the $i$th scatterplot. $k$ is the number of shapes allowed by the user.

thetab

A $n$ by $N$ matrix where the $i$th column is the vector of predicted values for the chosen shape for the $i$th scatterplot.

A $n$ by $1$ predictor vector, e.g., years.

Value

shapenum: the shapenum argument
pre.rate: annual rate of decline prior to the primary change point
pre.rate2: annual rate of decline prior to the secondary change point
dist.yr: year of the primary change points
dist2.yr: year of the secondary change points
dist.mag: difference in predicted values before and after primary change events
dist2.mag: difference in predicted values before and after secondary change events
dist.mag2: difference in predicted values before and after primary change points scaled by starting value
dist2.mag2: difference in predicted values before and after secondary change points scaled by starting value
dist.dur: duration of the change event before resuming a downward turn
dist2.dur: duration of the change event before resuming a downward turn
post.rate: annual rate of decline after the end of the primary change event
post2.rate: annual rate of decline after the end of the secondary change event
my.ic: information criteria value for the chosen shape

References

Moisen, G.G., M. Meyer, T.A. Schroeder, C. Toney, X. Liao, E.A. Freeman, K. Schleeweis. Shape-selection in Landsat time series: A tool for monitoring forest dynamics (In Review). Global Change Biology.

Examples

Run this code

## Not run: 
# 	# import the matrix of Landsat signals 
# 	data("ymat")
# 	
# 	# define the predictor vector: the year 1985 to the year 2010
# 	x <- 1985:2010
#  	
# 	# call the shape routine allowing a double-jump shape using "CIC"
# 	ans <- shape(x, ymat, "CIC")
# 
# 	# Example 1: parameters for a flat shape
# 	flat_id <- which(ans$shape == 1)
# 	i <- flat_id[1]
# 	ans_flat <- shapeparams(ans$shape[i], ans$ic[, i], ans$thetab[, i], x)	
# 
# 	# Example 2: parameters for a one-jump shape
# 	jp_id <- which(ans$shape == 3)
# 	i <- jp_id[1]
# 	ans_jp <- shapeparams(ans$shape[i], ans$ic[, i], ans$thetab[, i], x)	
# 
# 	# Example 3: parameters for a double-jump shape
# 	db_id <- which(ans$shape == 7)
# 	i <- db_id[1]
# 	ans_db <- shapeparams(ans$shape[i], ans$ic[, i], ans$thetab[, i], x)		
# ## End(Not run)