[ai-geostats] Help on estimating spatial volatilities
Greetings, I apologize in advance if this question is less coherent or well-formed than I would prefer, but I am hoping someone on the list can offer suggestions on the following topic. Briefly, I am working on a research problem in quantitative finance involving the use of options models to value mortgages written on large commercial real estate properties. Options model (such as the famous Black-Scholes equation) require the user to specify a volatility parameter, which is related to the variance of the value of the asset one is trying to model. Often one would simply calculate the standard deviation of historical prices on the asset (e.g., historical stock market prices) and use this estimate as the input into the model. For my particular problem, I have a large sample of data on commercial real estate sales for major cities in the United States. Each record is geocoded by the lat-long coordinate of the building. I have successfully built SAR models based upon Delaunay triangulation for the spatial matrix, so the data supports some reasonable geo-statistical modeling. Experience and past research suggests that the value of the mortgages is closely tied to the value of the properties, which show a significant degree of spatial correlation (on a city-by-city basis). I am trying to determine a way to estimate a vector of intra-city volatility parameters that reflect the underlying spatial correlation of the real estate data. I should also point out that this data is skewed and fat-tailed, so a reasonably flexible distribution would be ideal. Thanks in advance for any help that may be offered; and again I apologize if my inquiry is less than fully thought-out. Regards, Mark * By using the ai-geostats mailing list you agree to follow its rules ( see http://www.ai-geostats.org/help_ai-geostats.htm ) * To unsubscribe to ai-geostats, send the following in the subject or in the body (plain text format) of an email message to [EMAIL PROTECTED] Signoff ai-geostats
RE: AI-GEOSTATS: Help: spatial heterogeneity and autocorrelation indices
Title: Message About your question on heterogeneity in spatial data. Sorry formy very lazy answer but one elegant way to deal with such heterogeneity is Denis Allard's class kriging. See http://www.ai-geostats.org/papers/_papers/000e.htm Gregoire PS: I just have checked the ftp server of GIDA which is down at the moment, unfortunately. You could download the whole file of SIC97 from http://www.ai-geostats.org/events/sic97.htmwhere his paper is also published.
RE: AI-GEOSTATS: Help: spatial heterogeneity and autocorrelation indices
Hi, This is a question I have been scratching my head lately. In my data, there seems to be a global range, i.e. spatial autocorrelation does imply some sort of homogeneity throughout the whole area. However, if you look into more details, some of the sub-region contains outlier and hotspot which have totally differet local ranges than global ranges. So, the questions come as following: 1. Do we need to break up into different sub-regions (hetrogeneity) even you do have global range? 2. If so, how do you break the whole area into sub-regions? Can we use cluster anaylsis based on the minimum variances algorithms? Or can we optimze the area into differnt sub-regions based on the distributions of local range? Can we sperate the local range with global range? Getis (2001) paper discussed something about this, but I think there is a lot needs to be done. Anyone has any comments about this? Shing = Original Message From Chunhua Zhang [EMAIL PROTECTED] = Hello lists, I have a question: I am now interested in heterogeneity. Heterogeneity is related to pattern and pattern is absence of randomness. Many indices of spatial autocorrelation have been applied to study heterogeneity. From my understanding, spatial autocorrelation indices deals with spatial dependence, while it is a special case of spatial homogeneity. Therefore, is it reasonable to apply indices of homogeneity to pattern study? Thanks! Chunhua Shing-Tzong Lin Teaching and Research Assistant Department of Geography Texas State University, San Marcos (512)345-1935 -- * To post a message to the list, send it to [EMAIL PROTECTED] * 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 [EMAIL PROTECTED] 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 * Support to the list is provided at http://www.ai-geostats.org
AI-GEOSTATS: Help: spatial heterogeneity and autocorrelation indices
Hello lists,I have a question:I am now interested in heterogeneity. Heterogeneity is related to pattern and pattern is absence of randomness.Many indices of spatial autocorrelation have been applied to study heterogeneity. From my understanding, spatial autocorrelation indices deals with spatial dependence, while it is a special case of spatial homogeneity. Therefore, is it reasonable to apply indices of homogeneity topattern study? Thanks! Chunhua
AI-GEOSTATS: help with s-plus
Hello, I'm a PhD student trying to use S-Plus (with the spatial stats module) to create variogram clouds so that I can identify local outliers in my data set (I'm looking for local outliers and not general population outliers).. I have previously only used genstat for my geostats and I'm not finding the help files much help! If anyone knows S-Plus and can help with the following I'd be very grateful. I can plot the variogram cloud OK (this is easy as I can do it through the menus). However, what I need to be able to do is IDENTIFY the points in the plot. The is an identify command which you have to use in the command line, but I cannot get it to work for me. I've saved the plot, but s-plus can't find it when I refer back to it... even though I'm the in the right folder. Perhaps that isn't the main problem! Any help gratefully received! Jessica Lenham PhD Student University of Nottingham and British Geological Survey * This e-mail message, and any files transmitted with it, are confidential and intended solely for the use of the addressee. If this message was not addressed to you, you have received it in error and any copying, distribution or other use of any part of it is strictly prohibited. Any views or opinions presented are solely those of the sender and do not necessarily represent those of the British Geological Survey. The security of e-mail communication cannot be guaranteed and the BGS accepts no liability for claims arising as a result of the use of this medium to transmit from or to the BGS. The BGS cannot accept any responsibility for viruses, so please scan all attachments. http://www.bgs.ac.uk * -- * To post a message to the list, send it to [EMAIL PROTECTED] * 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 [EMAIL PROTECTED] 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 * Support to the list is provided at http://www.ai-geostats.org
AI-GEOSTATS: Help with Patch Analyst 2.2.
Dear all, I am a first time user of Patch Analyst 2.2 extension for ArcView. I've got an ArcView 3.1 shape file of a landscape with almost 100 000 patches and a thousand of hectares size. I followed the guidelines and the run of 'SPATIAL STATISTICS' produced a table with results. However, these are for only RUN 1 and seem to be for a sample of the data. For instance, the analysis was only for few number of patches and not for all of them. How can I have the results for all the patches in the landscape? I have not seen anything mentioned about RUNS in the PA Manual. Any help is always welcome. Thank you. Anthi Gkaraveli. = --- Dr. Anthi Gkaraveli GIS Landscape Ecologist Forest Authority of Magnesia Prefecture, Greece. EMail: [EMAIL PROTECTED] WWW URL: http://www.bangor.ac.uk/~afs005/anthi/ Want to chat instantly with your online friends? Get the FREE Yahoo! Messenger http://uk.messenger.yahoo.com/ -- * To post a message to the list, send it to [EMAIL PROTECTED] * 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 [EMAIL PROTECTED] 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 * Support to the list is provided at http://www.ai-geostats.org
AI-GEOSTATS: Help, please with spatial(?) correlation
Dear list members, I am a GIS programmer at Hungarian Central Statistical Office, and trying to make a work about statistical connections between time required to reach some source (e.g. the capitol, the border crossing points, or local civil services) and local social parameters (this first time the governmental tax/person - as an indicator of the income). I have computed the required time data via network analysis for each localities, and have the respond variable. Using R I have made some linear fittings between time as predictor and the paid tax/person as respondent, but, I suspect, the strong linear correlation I found is an outcome from the spatial autocorrelation in the tax data. I have mapped the local spatial autocorrelation for these data, and found that it shows positive, negative and insignificant spatial autocorrelations between the neighbours in large, well separated continuous areas. The same areal distribution is typical for the residuals from the linear correlation. My question is: should I use geostatistical methods based on variogram? The argument to support this method is: My predictor is a distance-like value - in fact the time which is a function of the available speed on the road segments and the distance between localities. The argument against this method: My data are not from spatially continual variable(s), because there is not living people between settlements. Or should I include a spatial lag - the local average of the data weighted by the inverse distance (time) - into the regression? I strongly suspect, that this later method is the better solution, but can someone direct me to a publication about similar work? Please, excuse me for this longish question. Thank you in advance Jozsef Fabian GIS programmes HCSO Hungary -- * To post a message to the list, send it to [EMAIL PROTECTED] * 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 [EMAIL PROTECTED] 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 * Support to the list is provided at http://www.ai-geostats.org
Re: AI-GEOSTATS: Help, please with spatial(?) correlation
On Fri, 7 Feb 2003 [EMAIL PROTECTED] wrote: Dear list members, I am a GIS programmer at Hungarian Central Statistical Office, and trying to make a work about statistical connections between time required to reach some source (e.g. the capitol, the border crossing points, or local civil services) and local social parameters (this first time the governmental tax/person - as an indicator of the income). I have computed the required time data via network analysis for each localities, and have the respond variable. Using R I have made some linear fittings between time as predictor and the paid tax/person as respondent, but, I suspect, the strong linear correlation I found is an outcome from the spatial autocorrelation in the tax data. This is an interesting analysis, with quite a lot of features. 1) What are the localities? Can their behaviour (as local councils etc.) affect the tax per capita? Or is the tax per capita more a result of the state of the local economy? Why per capita (tax comes from working people, not total population)? My guess would be that local economic conditions are the main driver. How does tax per capita correlate with firm formation, unemployment? 2) Have you tested the residuals of your linear model for spatial autocorrelation, or just the response variable? 3) How many distance variables are you using to measure isolation - the most isolated being a long way from a) the capital, b) a border crossing, and c) local services? 4) How many localities are you examining? How are you constructing the spatial weights matrix for calculating spatial autocorrelation? I have mapped the local spatial autocorrelation for these data, and found that it shows positive, negative and insignificant spatial autocorrelations between the neighbours in large, well separated continuous areas. The same areal distribution is typical for the residuals from the linear correlation. My question is: should I use geostatistical methods based on variogram? The argument to support this method is: My predictor is a distance-like value - in fact the time which is a function of the available speed on the road segments and the distance between localities. The argument against this method: My data are not from spatially continual variable(s), because there is not living people between settlements. I think that using geostatistical methods would be premature while quite a lot can still be done treating the data as spatial lattice data. I would worry about the different effects of eastern and western borders, and population density, across the country. Or should I include a spatial lag - the local average of the data weighted by the inverse distance (time) - into the regression? I strongly suspect, that this later method is the better solution, but can someone direct me to a publication about similar work? Please, excuse me for this longish question. Very interesting - please contact me off the list if you prefer. Roger Bivand Thank you in advance Jozsef Fabian GIS programmes HCSO Hungary -- Roger Bivand Economic Geography Section, Department of Economics, Norwegian School of Economics and Business Administration, Breiviksveien 40, N-5045 Bergen, Norway. voice: +47 55 95 93 55; fax +47 55 95 93 93 e-mail: [EMAIL PROTECTED] -- * To post a message to the list, send it to [EMAIL PROTECTED] * 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 [EMAIL PROTECTED] 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 * Support to the list is provided at http://www.ai-geostats.org
Re: AI-GEOSTATS: help on GS+ and sciencedirect
Hi, I have the 3.1 version of GS+ and everything is going ok, but when I ask for the program to make the color maps i get these crazy squares and nothing related to what I want. Also the example data that comes with the program also gives these crazy results. I've install the GS+ in a several computer computers and the result was the same, except in one laptop. Does any one has some idea or suggestion ??? I've have had a similar problem with GS+. Every time I tried to set the model parameter the values inserted became crazy, the same crazyness being true for kriging results. After contacting the producer of GS+ I found that the problem was a consequence of the international setting of my PC: I was using Italian standard and GS+ was not able to adapt itself to this setting. Suggestion: try to control your international setting (if you are using Windows 9x version, inspect in your Control Panel). Choose English (USA) as standard language and use . as decimal separator and , for thousands. Finally shootdown your PC and restart. ciao Claudio -- Claudio Cocheo Fondazione Salvatore Maugeri - IRCCS Centro di Ricerche Ambientali Via Svizzera, 16 35127 - Padova Italy Ph. +39 049 806 45 20 Fax +39 049 806 45 55 -- * To post a message to the list, send it to [EMAIL PROTECTED] * 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 [EMAIL PROTECTED] 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 * Support to the list is provided at http://www.ai-geostats.org
Re: AI-GEOSTATS: Help
Davide Unless you get software which allows you to code samples by 'individual', the simplest way is to output the calculated semi-variogram for each individual and then use a spreadsheet to combine them, weighted by the number of pairs in each case. Isobel Clark http://geoecosse.bizland.com Do You Yahoo!? Get your free @yahoo.co.uk address at http://mail.yahoo.co.uk or your free @yahoo.ie address at http://mail.yahoo.ie -- * To post a message to the list, send it to [EMAIL PROTECTED] * 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 [EMAIL PROTECTED] 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 * Support to the list is provided at http://www.ai-geostats.org
AI-GEOSTATS: help
I'm interested in multivariate spatial data expecially geostatistical data. Where can I find simulations using cokriging? Thanks. Aldo -- * To post a message to the list, send it to [EMAIL PROTECTED] * 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 [EMAIL PROTECTED] 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 * Support to the list is provided at http://www.ai-geostats.org
