Can any *spatstat* user explain to me why the two p-values obtained below
for an envelope test against CSR are so different? > data(swedishpines) > d<-swedishpines > plot(d) > mad.test(d,Kest,nsim=999,verbose=F) Maximum absolute deviation test of CSR Monte Carlo test based on 999 simulations Summary function: K(r) Reference function: theoretical Alternative: two.sided Interval of distance values: [0, 24] units (one unit = 0.1 metres) Test statistic: Maximum absolute deviation Deviation = observed minus theoretical data: d mad = 150.69, rank = 216, p-value = *0.216* > mad.test(d,*Lest*,nsim=999,verbose=F) Maximum absolute deviation test of CSR Monte Carlo test based on 999 simulations Summary function: L(r) Reference function: theoretical Alternative: two.sided Interval of distance values: [0, 24] units (one unit = 0.1 metres) Test statistic: Maximum absolute deviation Deviation = observed minus theoretical data: d mad = 2.9921, rank = 9, p-value = *0.009* *!!!* These data are dispersed relative to CSR: >kl<-envelope(d,Kest,nsim=999,correction="border") >plot(kl) Dave Unwin [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list [hidden email] https://stat.ethz.ch/mailman/listinfo/r-sig-geo |
Hi David,
This is very clearly explained in page 393 of Baddeley et al. 2015. Basically, the MAD test is affected by transformations of the summary function, with the L-function providing more powerful tests because of its stabilization of the variance. If you are interested in point pattern analysis I would recommend you to get a copy of this nice book. Cheers, Marcelino Adrian Baddeley, Ege Rubak, Rolf Turner (2015). Spatial Point Patterns: Methodology and Applications with R. London: Chapman and Hall/CRC Press. http://www.crcpress.com/Spatial-Point-Patterns-Methodology-and-Applications-with-R/Baddeley-Rubak-Turner/9781482210200/ El 21/04/2018 a las 18:05, David Unwin escribió: > Can any *spatstat* user explain to me why the two p-values obtained below > for an envelope test against CSR are so different? > > > >> data(swedishpines) >> d<-swedishpines >> plot(d) >> mad.test(d,Kest,nsim=999,verbose=F) > > > Maximum absolute deviation test of CSR > > Monte Carlo test based on 999 simulations > > Summary function: K(r) > > Reference function: theoretical > > Alternative: two.sided > > Interval of distance values: [0, 24] units (one unit = 0.1 metres) > > Test statistic: Maximum absolute deviation > > Deviation = observed minus theoretical > > > > data: d > > mad = 150.69, rank = 216, p-value = *0.216* > > > >> mad.test(d,*Lest*,nsim=999,verbose=F) > > > Maximum absolute deviation test of CSR > > Monte Carlo test based on 999 simulations > > Summary function: L(r) > > Reference function: theoretical > > Alternative: two.sided > > Interval of distance values: [0, 24] units (one unit = 0.1 metres) > > Test statistic: Maximum absolute deviation > > Deviation = observed minus theoretical > > > > data: d > > mad = 2.9921, rank = 9, p-value = *0.009* > > > > *!!!* > > > > These data are dispersed relative to CSR: > >> kl<-envelope(d,Kest,nsim=999,correction="border") >> plot(kl) > > Dave Unwin > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-Geo mailing list > [hidden email] > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > . > -- Marcelino de la Cruz Rot Depto. de Biología y Geología Física y Química Inorgánica Universidad Rey Juan Carlos Móstoles España _______________________________________________ R-sig-Geo mailing list [hidden email] https://stat.ethz.ch/mailman/listinfo/r-sig-geo |
Many thanks. It is a superb book and amazing value for money. My only
excuse is that I have not as yet got to page 392. Plotting the functions also makes it a lot clearer. Dave On 21 April 2018 at 22:50, Marcelino de la Cruz Rot < [hidden email]> wrote: > Hi David, > > This is very clearly explained in page 393 of Baddeley et al. 2015. > > Basically, the MAD test is affected by transformations of the summary > function, with the L-function providing more powerful tests because of its > stabilization of the variance. > > If you are interested in point pattern analysis I would recommend you to > get a copy of this nice book. > > > Cheers, > > Marcelino > > > Adrian Baddeley, Ege Rubak, Rolf Turner (2015). Spatial Point Patterns: > Methodology and Applications with R. London: Chapman and > Hall/CRC Press. > http://www.crcpress.com/Spatial-Point-Patterns-Methodology- > and-Applications-with-R/Baddeley-Rubak-Turner/9781482210200/ > > > > > > > El 21/04/2018 a las 18:05, David Unwin escribió: > >> Can any *spatstat* user explain to me why the two p-values obtained below >> for an envelope test against CSR are so different? >> >> >> >> data(swedishpines) >>> d<-swedishpines >>> plot(d) >>> mad.test(d,Kest,nsim=999,verbose=F) >>> >> >> >> Maximum absolute deviation test of CSR >> >> Monte Carlo test based on 999 simulations >> >> Summary function: K(r) >> >> Reference function: theoretical >> >> Alternative: two.sided >> >> Interval of distance values: [0, 24] units (one unit = 0.1 >> metres) >> >> Test statistic: Maximum absolute deviation >> >> Deviation = observed minus theoretical >> >> >> >> data: d >> >> mad = 150.69, rank = 216, p-value = *0.216* >> >> >> >> mad.test(d,*Lest*,nsim=999,verbose=F) >>> >> >> >> Maximum absolute deviation test of CSR >> >> Monte Carlo test based on 999 simulations >> >> Summary function: L(r) >> >> Reference function: theoretical >> >> Alternative: two.sided >> >> Interval of distance values: [0, 24] units (one unit = 0.1 >> metres) >> >> Test statistic: Maximum absolute deviation >> >> Deviation = observed minus theoretical >> >> >> >> data: d >> >> mad = 2.9921, rank = 9, p-value = *0.009* >> >> >> >> *!!!* >> >> >> >> These data are dispersed relative to CSR: >> >> kl<-envelope(d,Kest,nsim=999,correction="border") >>> plot(kl) >>> >> >> Dave Unwin >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> R-sig-Geo mailing list >> [hidden email] >> https://stat.ethz.ch/mailman/listinfo/r-sig-geo >> . >> >> > -- > Marcelino de la Cruz Rot > Depto. de Biología y Geología > Física y Química Inorgánica > Universidad Rey Juan Carlos > Móstoles España > > -- David J. Unwin Professor Emeritus in Geography Birkbeck, University of London Phone +44(0)1604 686526 Mobile: +44(0)7840 297239 (text preferred) SKYPE: david.unwin99 [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list [hidden email] https://stat.ethz.ch/mailman/listinfo/r-sig-geo |
Good morning
I hope you are well I have a question regarding the persp and perspPoints functions I have the x and y spatial coordinates and also the altitude of all these coordinates. However, despite consulting several manuals, I have as yet been unable to create a terrain elevation plot and also to plot the points. I have only managed to create a persp image showing density I would therefore appreciate very much if anyone could be so kind as to help Thank you very much Kind regards Nicholas On 22 April 2018 at 08:46, David Unwin <[hidden email]> wrote: > Many thanks. It is a superb book and amazing value for money. My only > excuse is that I have not as yet got to page 392. Plotting the functions > also makes it a lot clearer. > Dave > > On 21 April 2018 at 22:50, Marcelino de la Cruz Rot < > [hidden email]> wrote: > > > Hi David, > > > > This is very clearly explained in page 393 of Baddeley et al. 2015. > > > > Basically, the MAD test is affected by transformations of the summary > > function, with the L-function providing more powerful tests because of > its > > stabilization of the variance. > > > > If you are interested in point pattern analysis I would recommend you to > > get a copy of this nice book. > > > > > > Cheers, > > > > Marcelino > > > > > > Adrian Baddeley, Ege Rubak, Rolf Turner (2015). Spatial Point Patterns: > > Methodology and Applications with R. London: Chapman and > > Hall/CRC Press. > > http://www.crcpress.com/Spatial-Point-Patterns-Methodology- > > and-Applications-with-R/Baddeley-Rubak-Turner/9781482210200/ > > > > > > > > > > > > > > El 21/04/2018 a las 18:05, David Unwin escribió: > > > >> Can any *spatstat* user explain to me why the two p-values obtained > below > >> for an envelope test against CSR are so different? > >> > >> > >> > >> data(swedishpines) > >>> d<-swedishpines > >>> plot(d) > >>> mad.test(d,Kest,nsim=999,verbose=F) > >>> > >> > >> > >> Maximum absolute deviation test of CSR > >> > >> Monte Carlo test based on 999 simulations > >> > >> Summary function: K(r) > >> > >> Reference function: theoretical > >> > >> Alternative: two.sided > >> > >> Interval of distance values: [0, 24] units (one unit = 0.1 > >> metres) > >> > >> Test statistic: Maximum absolute deviation > >> > >> Deviation = observed minus theoretical > >> > >> > >> > >> data: d > >> > >> mad = 150.69, rank = 216, p-value = *0.216* > >> > >> > >> > >> mad.test(d,*Lest*,nsim=999,verbose=F) > >>> > >> > >> > >> Maximum absolute deviation test of CSR > >> > >> Monte Carlo test based on 999 simulations > >> > >> Summary function: L(r) > >> > >> Reference function: theoretical > >> > >> Alternative: two.sided > >> > >> Interval of distance values: [0, 24] units (one unit = 0.1 > >> metres) > >> > >> Test statistic: Maximum absolute deviation > >> > >> Deviation = observed minus theoretical > >> > >> > >> > >> data: d > >> > >> mad = 2.9921, rank = 9, p-value = *0.009* > >> > >> > >> > >> *!!!* > >> > >> > >> > >> These data are dispersed relative to CSR: > >> > >> kl<-envelope(d,Kest,nsim=999,correction="border") > >>> plot(kl) > >>> > >> > >> Dave Unwin > >> > >> [[alternative HTML version deleted]] > >> > >> _______________________________________________ > >> R-sig-Geo mailing list > >> [hidden email] > >> https://stat.ethz.ch/mailman/listinfo/r-sig-geo > >> . > >> > >> > > -- > > Marcelino de la Cruz Rot > > Depto. de Biología y Geología > > Física y Química Inorgánica > > Universidad Rey Juan Carlos > > Móstoles España > > > > > > > -- > > > David J. Unwin > Professor Emeritus in Geography > Birkbeck, University of London > Phone +44(0)1604 686526 Mobile: +44(0)7840 297239 (text preferred) > SKYPE: david.unwin99 > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-Geo mailing list > [hidden email] > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > -- Kind regards Nicholas Bradley PhD Candidate School of International Relations University of St Andrews [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list [hidden email] https://stat.ethz.ch/mailman/listinfo/r-sig-geo |
On 25/04/18 19:45, Nicholas Bradley wrote:
> Good morning > > I hope you are well > > I have a question regarding the persp and perspPoints functions > > I have the x and y spatial coordinates and also the altitude of all these > coordinates. However, despite consulting several manuals, I have as yet > been unable to create a terrain elevation plot and also to plot the points. > I have only managed to create a persp image showing density > > I would therefore appreciate very much if anyone could be so kind as to help. Please don't hijack threads. Your question has nothing to do with envelope tests. You have a new question, so start a new thread with an appropriate subject line. I shall shortly attempt to answer your question in such a new thread. cheers, Rolf Turner -- Technical Editor ANZJS Department of Statistics University of Auckland Phone: +64-9-373-7599 ext. 88276 _______________________________________________ R-sig-Geo mailing list [hidden email] https://stat.ethz.ch/mailman/listinfo/r-sig-geo |
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