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Follow-up Q Crimestat/Splancs AI-GEOSTATS: point pattern analysis/ R question

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  • Juliann Aukema
    I sent this a week or so ago and am resending because I haven t seen it show up. Apologies if it did show up for some of you. Hi thanks for the responses,
    Message 1 of 4 , Aug 29 1:37 PM
      I sent this a week or so ago and am resending because
      I haven't seen it show up. Apologies if it did show up
      for some of you.

      Hi thanks for the responses,

      Several people suggested using CrimeStat and one
      person sent an R script for Splancs (below). I've
      tried both of these with my data, trying to start as
      simply as possible, and I do get nice looking output
      when I put in the coordinates of all of my points
      (haven't made it to subsets yet). However, when I use
      CrimeStat with rectangular edge correction, my points
      appear to be dispersed -below the envelope for larger
      distances-(randomly distributed if I use no
      correction) and when I use the Splancs script, they
      appear to be aggregated -above the envelope for all
      distances. I used 100 simulation replicates for both
      methods. Any ideas why I would get such opposite
      results? Would it be the edge correction, differences
      in how L(d) is calculated, misinterpretation . . .? I
      must be missing something.

      Thanks a lot,


      Juliann

      > library(splancs)
      >
      > file<-"Filename.csv"
      >
      > point<-read.csv(file, header=TRUE, sep=";")
      >
      > box<-array(c(0,1000,1000,0,0,0,1000,1000),
      > dim=c(4,2))
      > s<-seq(0,500,5)
      > rep<-100
      >
      > pointk<-khat(as.points(point), box,s, newstyle=TRUE)
      > UL.khat<-Kenv.csr(length(point$x), box,rep, s)
      >
      > plot(s, sqrt(pointk$khat/pi)-s, type="l",
      >
      ylim=c(min(c(min(sqrt(pointk$khat/pi)-s),min(sqrt(UL.khat$lower/pi)-s)))-0.5
      >
      >
      ,max(c(max(sqrt(pointk$khat/pi)-s),max(sqrt(UL.khat$upper/pi)-s)))+0.5),
      >
      > main=paste(sub(".csv","",file),"_RK", sep=""),
      > xlab="Distance d (m)",
      > ylab="L(d)-d")
      > lines(s, sqrt(UL.khat$upper/pi)-s, lty=2)
      > lines(s, sqrt(UL.khat$lower/pi)-s, lty=2)
      > lines(s, s*0, lty=1)
      >
      > df<-data.frame(d=s, data=sqrt(pointk$khat/pi)-s,
      > upper=sqrt(UL.khat$upper/pi)-s,
      > lower=sqrt(UL.khat$lower/pi)-s)
      >
      > write.table(df,
      > paste(sub(".csv","",file),"_RK",rep,".csv", sep=""),
      >
      > sep=";", row.names=TRUE)
      >
      > write.table(sqrt(pointk$khats/pi),
      > paste(sub(".csv","",file),"_RKMap.csv",
      > sep=""), sep=";", row.names=TRUE)
      >
      > dev.copy2eps()
      >
      > shell(paste("move rplot.eps
      > ",sub(".csv","",file),"_RK",rep,".eps", sep=""))


      ----------Original Post---------------------------
      > At 14:05 19.08.2003 -0700, you wrote:
      > > Good afternoon. I realize this is slightly
      > >off-topic, but I thought it likely that someone on
      > >this list could help and we could take further
      > >discussion off-list.
      > > I have a mapped set of about 800 points in a
      > >Roughly rectangular plot and I would like to ask
      > what
      > >is the distribution of these points (random,
      > regular,
      > >aggregated, if aggregated- at what scale). I would
      > >then like to ask the same question about various
      > >subsets of points with respect to the underlying
      > >distribution of points. (For example, suppose all
      > the
      > >points have an aggregated distribution, is a subset
      > of
      > >points aggregated more/less than expected given the
      > >underlying aggregation). I thought Ripley's K would
      > be
      > >the way to go, but have been having trouble getting
      > it
      > >to work. I've been trying to do it in R. I've made
      > >some graphics in R, but I'm really a novice and I
      > find
      > >that the help (including the bit in the Venables
      > and
      > >Ripley S-Plus book) is not quite sufficient to get
      > me
      > >going with the spatial part (I've played with
      > >libraries Spatial, Spatstat, Splancs, GeoR).
      > > My questions are:
      > >---Is Ripley's K the way to go? Any suggestions on
      > >that? Would you recommend something else?
      > >---Software (preferably inexpensive)
      > recommendations?
      > >---Would anyone be willing to share an R program
      > that
      > >I could modify for my data and/or a sample or
      > partial
      > >data set to make sure I have my data structured
      > >correctly for a particular library/procedure? (I
      > found
      > >this was the best way to make progress in SAS, but
      > I
      > >don't know many R or S-Plus users).
      > >
      > >Thanks a lot.
      > >Juliann
      > >aukemaj@...
      > >
      > >
      > >__________________________________
      > >Do you Yahoo!?
      > >Yahoo! SiteBuilder - Free, easy-to-use web site
      > design software
      > >http://sitebuilder.yahoo.com
      > >
      > >--
      > >* To post a message to the list, send it to
      > ai-geostats@...
      > >* As a general service to the users, please
      > remember to post a summary of
      > >any useful responses to your questions.
      >
      === message truncated ===






      __________________________________
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      Yahoo! SiteBuilder - Free, easy-to-use web site design software
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    • Carolyn & Richard Block
      Juliann I am not certain that Ned Levine, the developer of CrimeStat, has read this. I will forward it to him. Normal edge corrections don t work very well
      Message 2 of 4 , Sep 1, 2003
        Juliann
        I am not certain that Ned Levine, the developer of CrimeStat, has read this.
        I will forward it to him. Normal edge corrections don't work very well
        in looking at point patterns of crime because incidents of crime tend to
        cluster at city boundaries and jurisdictional changes. The program may be
        less tested for edge corrections than other things; however, CrimeStat 3 is
        now under development. Notification of any corrections and problems would
        be welcome.
        Dick
        ----- Original Message -----
        From: "Juliann Aukema" <aukemaj@...>
        To: <ai-geostats@...>; "fs" <jaukema@...>
        Sent: Friday, August 29, 2003 3:37 PM
        Subject: Follow-up Q Crimestat/Splancs AI-GEOSTATS: point pattern analysis/
        R question


        > I sent this a week or so ago and am resending because
        > I haven't seen it show up. Apologies if it did show up
        > for some of you.
        >
        > Hi thanks for the responses,
        >
        > Several people suggested using CrimeStat and one
        > person sent an R script for Splancs (below). I've
        > tried both of these with my data, trying to start as
        > simply as possible, and I do get nice looking output
        > when I put in the coordinates of all of my points
        > (haven't made it to subsets yet). However, when I use
        > CrimeStat with rectangular edge correction, my points
        > appear to be dispersed -below the envelope for larger
        > distances-(randomly distributed if I use no
        > correction) and when I use the Splancs script, they
        > appear to be aggregated -above the envelope for all
        > distances. I used 100 simulation replicates for both
        > methods. Any ideas why I would get such opposite
        > results? Would it be the edge correction, differences
        > in how L(d) is calculated, misinterpretation . . .? I
        > must be missing something.
        >
        > Thanks a lot,
        >
        >
        > Juliann
        >
        > > library(splancs)
        > >
        > > file<-"Filename.csv"
        > >
        > > point<-read.csv(file, header=TRUE, sep=";")
        > >
        > > box<-array(c(0,1000,1000,0,0,0,1000,1000),
        > > dim=c(4,2))
        > > s<-seq(0,500,5)
        > > rep<-100
        > >
        > > pointk<-khat(as.points(point), box,s, newstyle=TRUE)
        > > UL.khat<-Kenv.csr(length(point$x), box,rep, s)
        > >
        > > plot(s, sqrt(pointk$khat/pi)-s, type="l",
        > >
        >
        ylim=c(min(c(min(sqrt(pointk$khat/pi)-s),min(sqrt(UL.khat$lower/pi)-s)))-0.5
        > >
        > >
        > ,max(c(max(sqrt(pointk$khat/pi)-s),max(sqrt(UL.khat$upper/pi)-s)))+0.5),
        > >
        > > main=paste(sub(".csv","",file),"_RK", sep=""),
        > > xlab="Distance d (m)",
        > > ylab="L(d)-d")
        > > lines(s, sqrt(UL.khat$upper/pi)-s, lty=2)
        > > lines(s, sqrt(UL.khat$lower/pi)-s, lty=2)
        > > lines(s, s*0, lty=1)
        > >
        > > df<-data.frame(d=s, data=sqrt(pointk$khat/pi)-s,
        > > upper=sqrt(UL.khat$upper/pi)-s,
        > > lower=sqrt(UL.khat$lower/pi)-s)
        > >
        > > write.table(df,
        > > paste(sub(".csv","",file),"_RK",rep,".csv", sep=""),
        > >
        > > sep=";", row.names=TRUE)
        > >
        > > write.table(sqrt(pointk$khats/pi),
        > > paste(sub(".csv","",file),"_RKMap.csv",
        > > sep=""), sep=";", row.names=TRUE)
        > >
        > > dev.copy2eps()
        > >
        > > shell(paste("move rplot.eps
        > > ",sub(".csv","",file),"_RK",rep,".eps", sep=""))
        >
        >
        > ----------Original Post---------------------------
        > > At 14:05 19.08.2003 -0700, you wrote:
        > > > Good afternoon. I realize this is slightly
        > > >off-topic, but I thought it likely that someone on
        > > >this list could help and we could take further
        > > >discussion off-list.
        > > > I have a mapped set of about 800 points in a
        > > >Roughly rectangular plot and I would like to ask
        > > what
        > > >is the distribution of these points (random,
        > > regular,
        > > >aggregated, if aggregated- at what scale). I would
        > > >then like to ask the same question about various
        > > >subsets of points with respect to the underlying
        > > >distribution of points. (For example, suppose all
        > > the
        > > >points have an aggregated distribution, is a subset
        > > of
        > > >points aggregated more/less than expected given the
        > > >underlying aggregation). I thought Ripley's K would
        > > be
        > > >the way to go, but have been having trouble getting
        > > it
        > > >to work. I've been trying to do it in R. I've made
        > > >some graphics in R, but I'm really a novice and I
        > > find
        > > >that the help (including the bit in the Venables
        > > and
        > > >Ripley S-Plus book) is not quite sufficient to get
        > > me
        > > >going with the spatial part (I've played with
        > > >libraries Spatial, Spatstat, Splancs, GeoR).
        > > > My questions are:
        > > >---Is Ripley's K the way to go? Any suggestions on
        > > >that? Would you recommend something else?
        > > >---Software (preferably inexpensive)
        > > recommendations?
        > > >---Would anyone be willing to share an R program
        > > that
        > > >I could modify for my data and/or a sample or
        > > partial
        > > >data set to make sure I have my data structured
        > > >correctly for a particular library/procedure? (I
        > > found
        > > >this was the best way to make progress in SAS, but
        > > I
        > > >don't know many R or S-Plus users).
        > > >
        > > >Thanks a lot.
        > > >Juliann
        > > >aukemaj@...
        > > >
        > > >
        > > >__________________________________
        > > >Do you Yahoo!?
        > > >Yahoo! SiteBuilder - Free, easy-to-use web site
        > > design software
        > > >http://sitebuilder.yahoo.com
        > > >
        > > >--
        > > >* To post a message to the list, send it to
        > > ai-geostats@...
        > > >* As a general service to the users, please
        > > remember to post a summary of
        > > >any useful responses to your questions.
        > >
        > === message truncated ===
        >
        >
        >
        >
        >
        >
        > __________________________________
        > Do you Yahoo!?
        > Yahoo! SiteBuilder - Free, easy-to-use web site design software
        > http://sitebuilder.yahoo.com
        >
        > --
        > * To post a message to the list, send it to ai-geostats@...
        > * As a general service to the users, please remember to post a summary of
        any useful responses to your questions.
        > * To unsubscribe, send an email to majordomo@... with no subject and
        "unsubscribe ai-geostats" followed by "end" on the next line in the message
        body. DO NOT SEND Subscribe/Unsubscribe requests to the list
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