courses | 1 Nov 20:29 2010

Introduction to R

Introduction to R. Three lessons in three weeks. Begins 5 November.
Discussion board open 24/7. R has more functions than any other
statistics language, plus a world-wide user base. $304  Discount of $50
for students, faculty, and research workers at academic and research
institutions and government employees.)  Write courses <at> statcourse.com to
obtain this discount.  For more information, see
http://statcourse.com/intro2R.htm

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Kim Elmore | 9 Nov 19:19 2010
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Spatial Point Patterns and EDF of Ghat

I think this falls under the heading of a stats question, but here goes, anyway:

I have S+SpatialStats and wish to compare algorithm outputs of object locations provided by two different algorithms. I want to investigate whether or not the spatial point patterns could have been generated by the same process (whatever that might be). I can't seem to find such a tool directly. But, if I use the Ghat function to generate and EDF of Ghat vs. distance, and then use the Kolmogorov-Smirnov goodness-of-fit test for the Ghat EDF, would I be able to say anything useful about the equivalence of the two processes?

Kim Elmore
--
Kim Elmore, Ph <!-- /* Style Definitions */ p.MsoNormal, li.MsoNormal, div.MsoNormal {mso-style-parent:""; margin:0pt; margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman"; mso-fareast-font-family:"Times New Roman";} <at> page Section1 {size:612.0pt 792.0pt; margin:72.0pt 90.0pt 72.0pt 90.0pt; mso-header-margin:36.0pt; mso-footer-margin:36.0pt; mso-paper-source:0;} div.Section1 {page:Section1;} -->

Kim Elmore, Ph.D. (PP SEL/MEL/Glider, N5OP, 2nd Class Radiotelegraph, GROL)

“There is no such thing as bad weather, only different kinds of good weather.” – John Ruskin

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Louis Bajuk-Yorgan | 11 Nov 23:37 2010

Develop, Scale and Deploy your analyses more easily with Spotfire S+ 8.2

Continuing our focus on providing the best commercial platform for
creating and sharing statistical analyses, TIBCO is proud to announce
the general availability of Spotfire S+ 8.2. This release focuses on
helping our customers scale their analyses to solve larger analytic
problems and to share and deploy their analyses more easily.

The Spotfire S+ Product Family

This release builds on the features of TIBCO Spotfire Statistics
Services 3.1 (formerly S+Server) to make it even easier to create S+ and
R-powered analytic applications for deployment through TIBCO Spotfire.
We have also released a new version of Spotfire Miner, which combines
drag-and-drop analytic workflows with S+ scripts. 

Scaling to solve larger analytic problems 

Spotfire S+ now supports Windows 64-bit desktop platforms, and delivers
much faster matrix operations for higher overall performance.  The new
Statistics Services view in the Eclipse-based Spotfire S+ Workbench
provides a way to monitor the allocation and status of your Spotfire S+
and R analytic jobs run through Statistics Services, helping you utilize
the resources of your cluster or grid as efficiently as possible. 

Easier, More Secure Deployment

Spotfire S+ 8.1 introduced the ability to submit
computationally-intensive scripts to a server. This release provides the
ability to track and manage those jobs directly from within the Spotfire
S+ Workbench. The new Statistics Services View also lets you deploy
packages and data files easily and securely to a server from the
Spotfire S+ Workbench. 

Updated Spotfire S+ Workbench

The Spotfire S+ Workbench, our modern Eclipse-based Integrated
Development Environment (IDE) for developing and debugging S+ code, has
been updated to the latest version of the Eclipse framework to provide a
seamless user experience between multiple platforms (Unix, Linux, and
32-bit and 64-bit versions of Windows).

Focus on Customer Feedback

Based on many customer requests, this release provides numerous
improvements, including data access enhancements (such as the ability to
import from specific sheets in an Excel workbook), improved consistency
of colors and shapes between graphics devices, and support for Windows
7.

Enhanced R Compatibility
This version includes new functions (and new arguments to existing
functions) to improve compatibility with R, making it easier to migrate
packages from R to Spotfire S+ and simplifying writing scripts
compatible with both Spotfire S+ and R.

For more information on Spotfire S+ 8.2, please visit our website at:

http://spotfire.tibco.com/products/s-plus/statistical-analysis-software.
aspx

For more information on deploy S+ and R-powered applications through
Statistics Services, please visit:

http://spotfire.tibco.com/products/statistics-services/predictive-analyt
ics.aspx

--------------------------
Lou Bajuk-Yorgan
Sr. Director, Product Management
Spotfire, TIBCO Software
206-802-2328
lbajuk <at> tibco.com
http://spotfire.tibco.com
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Kim Elmore | 17 Nov 23:50 2010
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Event counts within time spans

I'm still learning about how to use timedate objects and their kin.

I have a span of data in which I want to count the number of events (reports) that occur within contiguous time intervals, say 15 min. The data are arrayed in a data frame with one event per row. What's more, i want to filter based on thetype of report. I think the last part is easy, but what do I use to count the number of events within a prescribed period?

Kim Elmore
--
Kim Elmore, Ph <!-- /* Style Definitions */ p.MsoNormal, li.MsoNormal, div.MsoNormal {mso-style-parent:""; margin:0pt; margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman"; mso-fareast-font-family:"Times New Roman";} <at> page Section1 {size:612.0pt 792.0pt; margin:72.0pt 90.0pt 72.0pt 90.0pt; mso-header-margin:36.0pt; mso-footer-margin:36.0pt; mso-paper-source:0;} div.Section1 {page:Section1;} -->

Kim Elmore, Ph.D. (PP SEL/MEL/Glider, N5OP, 2nd Class Radiotelegraph, GROL)

“There is no such thing as bad weather, only different kinds of good weather.” – John Ruskin

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David L Lorenz | 18 Nov 15:56 2010
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Re: Event counts within time spans


Kim,
  I'm guessing that you have a data set with at least 2 columns one for the time of the event (timeDate), and one for the value. The function aggregateSeries can be used to produce a summary that you described.  For the example below, I have a data set called MD, with columns DT (time Date), and EV. The call to produce a count of event in each month is

with(MD, aggregateSeries(timeSeries(EV, DTt), FUN=length, pos=timeSeq('10/01/2002', '12/31/2005', by='months'), drop.empty=F))

  I'll leave it up to you to read the documentation to figure out what does what and to figure out how to create a 15-minute time sequence.
Dave


From: Kim Elmore <Kim.Elmore <at> noaa.gov>
To: s-news <at> lists.biostat.wustl.edu
Date: 11/17/2010 04:51 PM
Subject: [S] Event counts within time spans
Sent by: s-news-owner <at> lists.biostat.wustl.edu




I'm still learning about how to use timedate objects and their kin.

I have a span of data in which I want to count the number of events (reports) that occur within contiguous time intervals, say 15 min. The data are arrayed in a data frame with one event per row. What's more, i want to filter based on thetype of report. I think the last part is easy, but what do I use to count the number of events within a prescribed period?

Kim Elmore
--

Kim Elmore, Ph.D. (PP SEL/MEL/Glider, N5OP, 2nd Class Radiotelegraph, GROL)

“There is no such thing as bad weather, only different kinds of good weather.” – John Ruskin[attachment "kim_elmore.vcf" deleted by David L Lorenz/WRD/USGS/DOI] --------------------------------------------------------------------
This message was distributed by s-news <at> lists.biostat.wustl.edu.  To
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elvis Miller | 18 Nov 20:13 2010

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William Dunlap | 18 Nov 20:30 2010

Re: Event counts within time spans

Here are some ways to make sequences of times at
15 minute intervals.  The key is to use timeSeq with
by="minutes" and k.by=15.
 
> start <- timeDate("2010-10-01",in.format="%y-%m-%d",format=getOption("time.out.format"))
> timeSeq(from=start, len=7, by="minutes", k.by=15)
[1] 10/01/2010 00:00:00.000 10/01/2010 00:15:00.000
[3] 10/01/2010 00:30:00.000 10/01/2010 00:45:00.000
[5] 10/01/2010 01:00:00.000 10/01/2010 01:15:00.000
[7] 10/01/2010 01:30:00.000
> fourDays <- timeSeq(from=start, to=start+4, by="minutes", k.by=15)
> head(fourDays)
[1] 10/01/2010 00:00:00.000 10/01/2010 00:15:00.000
[3] 10/01/2010 00:30:00.000 10/01/2010 00:45:00.000
[5] 10/01/2010 01:00:00.000 10/01/2010 01:15:00.000
> tail(fourDays)
[1] 10/04/2010 22:45:00.000 10/04/2010 23:00:00.000
[3] 10/04/2010 23:15:00.000 10/04/2010 23:30:00.000
[5] 10/04/2010 23:45:00.000 10/05/2010 00:00:00.000
 

Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com

 

From: s-news-owner <at> lists.biostat.wustl.edu [mailto:s-news-owner <at> lists.biostat.wustl.edu] On Behalf Of David L Lorenz
Sent: Thursday, November 18, 2010 6:56 AM
To: Kim Elmore
Cc: s-news <at> lists.biostat.wustl.edu; s-news-owner <at> lists.biostat.wustl.edu
Subject: Re: [S] Event counts within time spans


Kim,
  I'm guessing that you have a data set with at least 2 columns one for the time of the event (timeDate), and one for the value. The function aggregateSeries can be used to produce a summary that you described.  For the example below, I have a data set called MD, with columns DT (time Date), and EV. The call to produce a count of event in each month is

with(MD, aggregateSeries(timeSeries(EV, DTt), FUN=length, pos=timeSeq('10/01/2002', '12/31/2005', by='months'), drop.empty=F))

  I'll leave it up to you to read the documentation to figure out what does what and to figure out how to create a 15-minute time sequence.
Dave


From: Kim Elmore <Kim.Elmore <at> noaa.gov>
To: s-news <at> lists.biostat.wustl.edu
Date: 11/17/2010 04:51 PM
Subject: [S] Event counts within time spans
Sent by: s-news-owner <at> lists.biostat.wustl.edu




I'm still learning about how to use timedate objects and their kin.

I have a span of data in which I want to count the number of events (reports) that occur within contiguous time intervals, say 15 min. The data are arrayed in a data frame with one event per row. What's more, i want to filter based on thetype of report. I think the last part is easy, but what do I use to count the number of events within a prescribed period?

Kim Elmore
--

Kim Elmore, Ph.D. (PP SEL/MEL/Glider, N5OP, 2nd Class Radiotelegraph, GROL)

“There is no such thing as bad weather, only different kinds of good weather.” – John Ruskin[attachment "kim_elmore.vcf" deleted by David L Lorenz/WRD/USGS/DOI] --------------------------------------------------------------------
This message was distributed by s-news <at> lists.biostat.wustl.edu.  To
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Kim Elmore | 18 Nov 21:26 2010
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Re: Event counts within time spans

This is *exactly* what I need! I also learned a fair bit from your one-line example, so thank you very much, Dave!

Kim Elmore

On 11/18/2010 8:56 AM, David L Lorenz wrote:

Kim,
  I'm guessing that you have a data set with at least 2 columns one for the time of the event (timeDate), and one for the value. The function aggregateSeries can be used to produce a summary that you described.  For the example below, I have a data set called MD, with columns DT (time Date), and EV. The call to produce a count of event in each month is

with(MD, aggregateSeries(timeSeries(EV, DTt), FUN=length, pos=timeSeq('10/01/2002', '12/31/2005', by='months'), drop.empty=F))

  I'll leave it up to you to read the documentation to figure out what does what and to figure out how to create a 15-minute time sequence.
Dave


From: Kim Elmore <Kim.Elmore <at> noaa.gov>
To: s-news <at> lists.biostat.wustl.edu
Date: 11/17/2010 04:51 PM
Subject: [S] Event counts within time spans
Sent by: s-news-owner <at> lists.biostat.wustl.edu




I'm still learning about how to use timedate objects and their kin.

I have a span of data in which I want to count the number of events (reports) that occur within contiguous time intervals, say 15 min. The data are arrayed in a data frame with one event per row. What's more, i want to filter based on thetype of report. I think the last part is easy, but what do I use to count the number of events within a prescribed period?

Kim Elmore
--

Kim Elmore, Ph.D. (PP SEL/MEL/Glider, N5OP, 2nd Class Radiotelegraph, GROL)

“There is no such thing as bad weather, only different kinds of good weather.” – John Ruskin[attachment "kim_elmore.vcf" deleted by David L Lorenz/WRD/USGS/DOI] --------------------------------------------------------------------
This message was distributed by s-news <at> lists.biostat.wustl.edu.  To
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--
Kim Elmore, Ph <!-- /* Style Definitions */ p.MsoNormal, li.MsoNormal, div.MsoNormal {mso-style-parent:""; margin:0pt; margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman"; mso-fareast-font-family:"Times New Roman";} <at> page Section1 {size:612.0pt 792.0pt; margin:72.0pt 90.0pt 72.0pt 90.0pt; mso-header-margin:36.0pt; mso-footer-margin:36.0pt; mso-paper-source:0;} div.Section1 {page:Section1;} -->

Kim Elmore, Ph.D. (PP SEL/MEL/Glider, N5OP, 2nd Class Radiotelegraph, GROL)

“There is no such thing as bad weather, only different kinds of good weather.” – John Ruskin

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Avi Pfeffer | 22 Nov 22:59 2010

UAI 2011 Call for Papers (corrected)

Apologies for the duplicate post – this post corrects some errors in the previous version.

 

UAI 2011 Call for Papers

The 27th Conference on Uncertainty in Artificial Intelligence (UAI 2011) will be located in Barcelona, Spain, on July 14-17, 2011. Sessions will be held at the Campus Roger de Lluria of the Universitat Pompeu Fabra (UPF). The conference will happen just before the International Joint Conference on Artificial Intelligence (IJCAI).

UAI is the premier conference on issues relating to representation and management of uncertainty within the field of Artificial Intelligence. UAI is supported by the Association for Uncertainty in Artificial Intelligence (AUAI).

We encourage submissions that report on theoretical or methodological advances in modeling, inference, learning and decision making under uncertainty. Submissions reporting on novel and insightful applications of these techniques within intelligent systems are also strongly encouraged. Examples of such application areas include, but are not limited to, computational biology, computer vision, speech processing, computational linguistics, information retrieval, medical systems, multi-agent systems, robotics, and sensor networks.

IMPORTANT DATES

  • Friday, March 18 2011, midnight GMT: UAI full paper submission

  • Friday, April 29 2011: Reviews available.

  • Thursday, May 5 2011, midnight GMT: Author feedback due.

  • Wednesday, June 1 2011: Author notification.

  • Friday, June 17 2011: Camera ready due.

NOTE: midnight GMT = 7pm EST = 4pm PST

Paper Submission Details

UAI 2011 requires electronic submission of papers and abstracts, inserted in the confmaster system (http://uai.confmaster.net). Reviewing will be double-blind, so authors should take care not to reveal their identities in their submission.

A regular submitted paper should not be under review by any other conference at the time it is submitted to UAI 2011 nor at any time during the reviewing period of UAI 2011. At the time of submission, a regular paper should also not have already been accepted for publication in a journal. The standard UAI paper length is eight (8) pages, including all figures and bibliography. Authors may optionally purchase up to two (2) additional pages for a fee, the cost of which will be determined later (in 2010 it was $150US/page). We note that the confmaster paper submission site allows the optional submission of supplementary material up to length 5MBs, which may contain proofs, background material, and so on in support of the UAI2011 anonymous submission.

UAI has traditionally mostly attracted submissions from computer scientists, even though reasoning under uncertainty is an important topic in many other areas such as statistics, economics and philosophy. To accommodate the publishing traditions of these fields, authors may submit working papers that are under review in a journal, as NOT-FOR-PROCEEDINGS submissions. These submissions will be subject to review and considered for presentation at the conference but not for publication in the proceedings. These submissions need not conform to the conference paper format. Abstracts (max. 1 page) of accepted working papers will be included in the proceedings and must be coupled with a URL that points to the full paper and that will be reliable for at least two years. Open access is strongly preferred although the paper can be hosted by a publisher who takes copyright and limits access, as long as there is a link to the location.

Presentation, Proceedings and Awards

Accepted papers will be presented at the conference in either plenary or poster sessions. At least one of the paper's authors should be present at the conference to present the work. All accepted papers will be included in the Proceedings of the Twenty Seventh Conference on Uncertainty in Artificial Intelligence. The program committee will select papers for special distinction in two categories at UAI 2011: a "Best Paper" award, and a "Best Student Paper" award. The conference home page will contain instructions for certifying student status with regards to the latter award.

 

 
 
 
 

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