Hello! I have a dataset with the following two vectors: year<-c(1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009) piproute<-c(0.733333333,0.945945946,1.886363636,1.607843137,4.245614035,3.175675676,2.169014085,2,2.136363636,2.65625,2.080645161,2.114754098,2.090909091,3.012195122,2.935897436,2.592105263,1.075757576,1.210526316,1,1.1875,1.903614458,1.385542169,1.788990826,1.163793103,1.558558559,1.595238095,1.758333333,1.858267717,2.169117647,1.403225806,2.859375,3.236220472,2.054263566,3.854166667,1.812080537,2.708029197,2.75862069,2.625954198,4.540740741,3.686567164,2.8,2.968253968,3.517730496) Pipits is the response variable (it is the number of birds counted at each survey site in each year) and year is the independent variable. If you plot it in R (plot(year,piproute,pch=19)), you'll see that the relationship looks like a quintic polynomial. Initially I was trying to fit this curve using an iterative equation, but it's not working. I suspect that the curve-fitting equation itself is inappropriate (it's a modified version of the logistic growth equation). Now what I'd like to do is identify the 3 break/inflection points in the population trend. That way, I can make an argument that the break points corresponded to shifts in government policy with respect to land use management. I've been looking at the segmented package, and initially I looked at change.pt test in the circ.stats package (which is inappropriate b/c my data is not amenable to circular statistical analysis). Any ideas on what I could do would be appreciated! Thank you! -Charlotte
Charlotte, Try: birds.lo <- loess(piproute~year,span=.25) # play with span to see your desired pattern birds.pr<-predict(birds.lo, data.frame(year = seq(1967, 2009, 1)), se = FALSE) # plot($year,birds.pr$fit,ylim=c(0,5)) par(new=T) plot(year,birds.pr$fit,pch="+",col=2,ylim=c(0,5)) -- Clint Bowman INTERNET: clint at ecy.wa.gov Air Quality Modeler INTERNET: clint at math.utah.edu Department of Ecology VOICE: (360) 407-6815 PO Box 47600 FAX: (360) 407-7534 Olympia, WA 98504-7600 On Mon, 26 Apr 2010, Charlotte Chang wrote:> Hello! > I have a dataset with the following two vectors: > > year<-c(1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009) > > piproute<-c(0.733333333,0.945945946,1.886363636,1.607843137,4.245614035,3.175675676,2.169014085,2,2.136363636,2.65625,2.080645161,2.114754098,2.090909091,3.012195122,2.935897436,2.592105263,1.075757576,1.210526316,1,1.1875,1.903614458,1.385542169,1.788990826,1.163793103,1.558558559,1.595238095,1.758333333,1.858267717,2.169117647,1.403225806,2.859375,3.236220472,2.054263566,3.854166667,1.812080537,2.708029197,2.75862069,2.625954198,4.540740741,3.686567164,2.8,2.968253968,3.517730496) > > Pipits is the response variable (it is the number of birds counted at > each survey site in each year) and year is the independent variable. > If you plot it in R (plot(year,piproute,pch=19)), you'll see that the > relationship looks like a quintic polynomial. > > Initially I was trying to fit this curve using an iterative equation, > but it's not working. I suspect that the curve-fitting equation itself > is inappropriate (it's a modified version of the logistic growth > equation). Now what I'd like to do is identify the 3 break/inflection > points in the population trend. That way, I can make an argument that > the break points corresponded to shifts in government policy with > respect to land use management. I've been looking at the segmented > package, and initially I looked at change.pt test in the circ.stats > package (which is inappropriate b/c my data is not amenable to > circular statistical analysis). Any ideas on what I could do would be > appreciated! > > Thank you! > > -Charlotte > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >
You can try this:
library(inflection)
#you have to instsall package inflection first
a<-findiplist(cbind(year),cbind(piproute),1)
a
The answer:
[,1] [,2] [,3]
[1,] 5 35 1986.0
[2,] 5 30 1983.5
shows that the total inflection point is between 1983 and 1986, if we treat
data as first concave and then convex, as it can be found from a simple
graph.
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You can try this:
library(inflection)
#you have to instsall package inflection first
a<-findiplist(cbind(year),cbind(piproute),1)
a
The answer:
[,1] [,2] [,3]
[1,] 5 35 1986.0
[2,] 5 30 1983.5
shows that the total inflection point is between 1983 and 1986, if we treat
data as first concave and then convex, as it can be found from a simple
graph.
--
View this message in context:
http://r.789695.n4.nabble.com/Identifying-breakpoints-inflection-points-tp2065886p4669117.html
Sent from the R help mailing list archive at Nabble.com.