eugene dalt | 2 Feb 01:55 2010
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Any R course in San Francisco the last 2 weeks of February?

Hi folks,

I will be on vacation with my parents in San Francisco the last 2 weeks of February and wondering if there are
upcoming short R courses in San Francisco during that time so I could attend.

Please send me the links - 

Thank you - Eugene

      
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wic-office | 2 Feb 10:47 2010

IEEE/WIC/ACM WI 2010 - Call for Papers


[Apologies if you receive this more than once]

#####################################################################
         IEEE/WIC/ACM WEB INTELLIGENCE 2010 
                  CALL FOR PAPERS
#####################################################################

2010 IEEE/WIC/ACM International Conference on Web Intelligence (WI-10)

August 31 - September 3, 2010, York University, Toronto, Canada

http://www.yorku.ca/wiiat10

Sponsored By
IEEE Computer Society
Web Intelligence Consortium (WIC)
Association for Computing Machinery (ACM)

##################################################################
# Papers Due: *** March 26, 2010 ***
# Accepted papers will be published in the conference proceedings
# by the IEEE Computer Society Press.
##################################################################

WI 2010 will provide a leading international forum of scientific
research and development to explore the fundamental interactions
between AI-engineering and Advanced Information Technology 
(e.g., wireless networks, ubiquitous devices, social networks, and
data/knowledge grids), and their role on the next generation of
(Continue reading)

Peter Hingley | 2 Feb 16:01 2010

Peter Hingley is out of the office.


I will be out of the office starting  02-02-2010 and will not return until
08-02-2010.

I will respond to your message when I return.

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elvis@xlsolutions-corp.com | 2 Feb 21:23 2010

February/March 2010*** R / S-PLUS Courses*** by XLSolutions Corp in San Francisco and other USA cities

Check out our February/March R / S-PLUS courses schedule in San
Francisco and
other USA cities.

http://www.xlsolutions-corp.com/Rcourses

*** S-PLUS / R : Programming Essentials.
*** R/S+ Fundamentals and Programming Techniques
*** R/S-PLUS Functions by Example.
*** S/R-PLUS Programming 3: Advanced Techniques and Efficiencies.

More on website

http://www.xlsolutions-corp.com/rplus.asp 

Ask for group discount and reserve your seat Now - Earlybird Rates.
Payment due after the class! Email Sue Turner:  sue at
xlsolutions-corp.com

Phone:               206-686-1578         

Please let us know if you and your colleagues are interested in this
class to take advantage of group discount. Register now to secure your
seat.

Cheers,
Elvis Miller, PhD
Manager Training.
XLSolutions Corporation
206 686 1578         
(Continue reading)

Jan Ivanouw | 2 Feb 21:45 2010
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Simple NA-substitution problem

I am sorry not being able to solve this simple problem by myself, but I would appreciate very much any help.
 
I have a data frame with many variables and a lot of NA's dispersed around in the df.
Now, I have to eksport the data frame for use in another program which cannot use the alfanumeric code 'NA', so I have to substitute an integer which then can be marked as 'missing' in the other program.
 
But how do I substitute all NA's in the df with for instance the number '9' ?
 
Best,
 
Jan Ivanouw PhD
University of Copenhagen
Denmark
gerald.jean | 2 Feb 22:07 2010
Picon

RE Simple NA-substitution problem

Hello Jan,

suppose your data frame is named "df", then:

df[is.na(df)] <- 9

will do the trick.

Have fun,

Gérald Jean
Conseiller senior en statistiques,
VP Planification et Développement des Marchés,
Desjardins Groupe d'Assurances Générales
télephone            : (418) 835-4900 poste (7639)
télecopieur          : (418) 835-6657
courrier électronique: gerald.jean <at> dgag.ca

"In God we trust, all others must bring data"  W. Edwards Deming

                                                                           
             "Jan Ivanouw"                                                 
             <ivanouw <at> post8.te                                             
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             Envoyé par :              <s-news <at> lists.biostat.wustl.edu>    
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                                       [S] Simple NA-substitution problem  

             2010/02/02 15:46                                              

                                                                           
             Veuillez répondre                                             
                     à                                                     
             s-news <at> lists.bios                                             
               tat.wustl.edu                                               

I am sorry not being able to solve this simple problem by myself, but I
would appreciate very much any help.

I have a data frame with many variables and a lot of NA's dispersed around
in the df.
Now, I have to eksport the data frame for use in another program which
cannot use the alfanumeric code 'NA', so I have to substitute an integer
which then can be marked as 'missing' in the other program.

But how do I substitute all NA's in the df with for instance the number '9'
?

Best,

Jan Ivanouw PhD
University of Copenhagen
Denmark

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Jaime Lloret Mauri | 2 Feb 23:02 2010
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1st CfP: ICWMC 2010 || September 20-25, 2010 - Valencia, Spain


INVITATION:

=================
Please consider to contribute to and/or forward to the appropriate groups the following opportunity to
submit and publish original scientific results.
=================

============== ICWMC 2010 | Call for Papers ===============

CALL FOR PAPERS, TUTORIALS, PANELS

ICWMC 2010: The Sixth International Conference on Wireless and Mobile Communications 
September 20-25, 2010 - Valencia, Spain

General page: http://www.iaria.org/conferences2010/ICWMC10.html
Call for Papers: http://www.iaria.org/conferences2010/CfPICWMC10.html

Submission deadline: April 20, 2010

Sponsored by IARIA, www.iaria.org
Co-sponsored by: IEEE Spain, University 'Politehnica' Bucharest, La Machinista Valenciana,
Universidad Politecnica de Valencia, IGIC 

Extended versions of selected papers will be published in IARIA Journals: http://www.iariajournals.org
Publisher: CPS ( see: http://www2.computer.org/portal/web/cscps )
Archived: IEEE CSDL (Computer Science Digital Library) and IEEE Xplore
Submitted for indexing: Elsevier's EI Compendex Database, EI's Engineering Information Index
Other indexes are being considered: INSPEC, DBLP, Thomson Reuters Conference Proceedings Citation Index

Please note the Poster Forum and Work in Progress options.

The topics suggested by the conference can be discussed in term of concepts, state of the art, research,
standards, implementations, running experiments, applications, and industrial case studies.
Authors are invited to submit complete unpublished papers, which are not under review in any other
conference or journal in the following, but not limited to, topic areas. 

All tracks are open to both research and industry contributions, in terms of Regular papers, Posters, Work
in progress, Technical/marketing/business presentations, Demos, Tutorials, and Panels.

Before submission, please check and conform with the Editorial rules: http://www.iaria.org/editorialrules.html

ICWMC 2010 Tracks (tracks' topics and submission details: see CfP on the site)

Wireless Communications Basics
Coding & modulation & equalization; Channel modeling and characterization;
Equalization/Synchronization; Transform-domain communication; Multiple access algorithms and
schemes; Antenna and RF subsystems; Smart antennas, adaptive antennas, MIMO and beam forming; MIMO and
OFDM Based PHY Layer technologies; CDMA Systems

Radio Interfaces and Systems
Radio communications systems; Radio resource management; Radio transmission technologies; Power and
interference control; Interference Cancellation for Wireless Mobile Systems; Power management for
small terminals; Energy map; Channel Measurement and Characterization

Spectrum Allocation and Management
Spectrum efficiency analyses; Dynamic spectrum access networks; Spectrum management; Interference
mitigation and management techniques 

Circuits for Wireless Communications
Wireless ASICs; Wireless technologies; RF Design issues

Wireless and Mobility
Mobility management; Location-based services and positioning; Micro and macro-mobility; Mobility,
location and handoff management; Mobile and wireless IP; Wireless broadband mobile access; Routing in
multihop, ad hoc and sensor networks; Wireless multicasting; Wireless mesh networks; Topology control
in wireless

Protocols for wireless and mobility
Wireless protocols, architectural and design concepts; Protocols for air interfaces and networks;
Wireless MAC protocols: Design and analysis; Transport layer issues in mobile and wireless networks;
Middleware for handhelds and mobile services nodes; Proxies and middleware for wireless networks 

Traffic and congestion control, QoS, Resource Management
Traffic Modeling and Analysis; 3G/4G Bandwidth on Demand; QoS and mobility; End-to-end QoS; QoS
profiling and pricing; Traffic Engineering; Congestion and admission control 

Wireless and mobile technologies
Wireless LANs; Home and Personal Area Networks: Bluetooth, ZigBeee, etc; Wireless MANs:802.16, 802.20;
Wireless WANs: 2G/3G/4G; Mobile ad hoc networks and multi-hop wireless; Sensor networks and
applications; Ultra-wideband and short-range networks; High altitude platforms and satellites;
Emergency wireless communications; Wireless real-time communications 

Performance Evaluation, Simulation and Modeling of wireless networks and systems
Performance and QoS in wireless networks; Radio channel modeling (wave propagation and measurements);
Mobile/wireless networks modeling and simulation; Performance of end-to-end protocols over wireless
networks 

Management of wireless and mobile networks 
Mobility and QoS management; Billing technologies and tools; Policy Based Management in wireless LANS
and MANs; Wireless and Mobile Network Planning; Mobile Database Access and Design

Security in wireless and mobile environment
Security and robustness in wireless networks; Privacy, Authentication Authorization and Accounting
(AAA); Encryption and Cryptography; Key Management Protocols; Digital Rights Management and
Multimedia Protection

Networks convergence and integration
2G/3G/4G integration; Convergence of 3G wireless and Internet cross-layer design in wireless networks;
WLAN/3G/4G integration; Wireless-wireline convergence; Heterogeneous Networks (WAN, Wireless MAN,
WLAN); IP Multimedia subsystems (IMS); Next Generation Network Architecture- mobility issues;
Coexistence of mobile radio networks; End to End QoS in Heterogeneous environment; Signaling for
integrated wireline/wireless networks 

Applications and services based on wireless infrastructures
Mobile & Wireless applications & services; Service discovery: protocols and frameworks; Personalized
services and applications; Audio-visual and mobile multimedia applications; Media and content
distribution over wireless networks 

Standardization and regulations
Position on standards & fora on wireless and mobile networks; Wireless Networks Standards and Protocols;
Communications regulations; 802.11 WLAN Standards; 802.16 WMAN Standards; 3GPP and 3GPP2 standards;
HSDPA Technology and Standards; Next Generation Network standards 

Design and implementation 
Emerging wireless technologies; Cross-layer optimizations in wireless networks; Design and
implementation of mobile information systems; Software defined radio and re-configurability; Joint
PHY/MAC design 

Wireless and mobile network deployment
Business models on wireless networks; Market trends and regional developments; M-commerce; Lessons
learnt for wireless deployment in schools Lessons learnt for wireless deployment in special regions;
Specialized wireless networks; Heterogeneous wireless network deployment (e.g., combining 802.11,
802.16 and 3G networks)

Cooperative and Cognitive Vehicular Networks
Architectures and platforms of cognitive vehicular network; Distributed artificial intelligence
techniques for cognitive networks; Cognitive vehicular routing metrics and supporting protocols;
Reduced complexity cognitive networks; Physical and MAC layer issues; Protocols design for cognitive
vehicular networks; Cross-layer optimization in cognitive networks; Security issues for vehicular
and cognitive networks; Testbed experiment, applications and new advances; Cooperative vehicular
networks; QoS provisioning in heterogeneous networks ; Managing vertical handover; Multihoming; IPv6
GeoNetworking; Vehicular network architectures and protocols ; Cross-layer design and optimization
for vehicular networks and cognitive networks; Mobility management and topology control;
Standardization and De
 velopment of vehicular networks

Convergence and social mobility
Convergence of mobile networks with the Web 2.0; Convergence on architecture and services; Open service
capabilities; Open exposure of telco capabilities; Open Web APIs, SOA and SDP); Interworking
strategies; Mobile terminals as sources for User-generated content; Architecture and services for
user-generated content; Auto-description and metadata synthesis for telecom-generated for
user-generated content; Social mobile networks; User behavior profiling; Social connections (social
graphs, contacts, etc); Services and architectures/solutions for social mobile services

==========
ICWMC GENERAL CHAIR
Jaime Lloret Mauri, Polytechnic University of Valencia, Spain 

ICWMC Advisory Chairs
Silviu Ciochina, University 'Politehnica' Bucharest, Romania 
Petre Dini, Concordia University, Canada / IARIA, USA
Tudor Palade, Technical University of Cluj-Napoca, Romania 
Francisco Ramos, Polytechnic University of Valencia, Spain 

ICWMC 2010 Research Institute Liaison Chairs
Nicolae Crisan, Technical University of Cluj-Napoca, Romania 
Adrian Matei, Politehnica University of Bucharest / Orange Romania S.A., Romania 
Jyrki Penttinen, Nokia Siemens Networks - Madrid, Spain / Helsinki University of Technology, Finland 
Tomi Rty, VTT Technical Research Centre of Finland, Finland 
Javier Del Ser Lorente, Tecnalia, Spain 

ICWMC 2010 Industry/Research Chairs
Jos Garca, La Maquinista Valenciana, Spain 
Jingli Li, TopWorx - Emerson, USA 
Christopher Nguyen, Intel Corp., USA 
Horia Stefanescu, Orange, Romania 

ICWMC 2010 Special Area Chairs
Cooperative and Cognitive Vehicular Networks Area Chairs:
Yacine Khaled, Geenov, France
Jong-Hyouk Lee, Sungkyunkwan University, Korea // INRIA, France

Committee members: http://www.iaria.org/conferences2010/ComICWMC10.html
====================
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Madeline Bauer | 2 Feb 23:47 2010
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Re: RE Simple NA-substitution problem

Jan, You might want to use a number like -99 to make sure that the 
number you use to show missing is not in the range of your known data.
Cheers!
Madeline
USC
At 01:07 PM 02/02/2010, gerald.jean <at> dgag.ca wrote:
>Hello Jan,
>
>suppose your data frame is named "df", then:
>
>df[is.na(df)] <- 9
>
>will do the trick.
>
>Have fun,
>
>G=E9rald Jean
>Conseiller senior en statistiques,
>VP Planification et D=E9veloppement des March=E9s,
>Desjardins Groupe d'Assurances G=E9n=E9rales
>t=E9lephone            : (418) 835-4900 poste (7639)
>t=E9lecopieur          : (418) 835-6657
>courrier =E9lectronique: gerald.jean <at> dgag.ca
>
>"In God we trust, all others must bring data"  W. Edwards Deming
>
>
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20
>              "Jan Ivanouw"=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20
>              <ivanouw <at> post8.te=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20
>              le.dk>                                                      A=
>=20
>              Envoy=E9 par :              <s-news <at> lists.biostat.wustl.edu>=
>=20=20=20=20
>              s-news-owner <at> list                                          cc=
>=20
>              s.biostat.wustl.e=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20
>              du                                                      Objet=
>=20
>                                        [S] Simple NA-substitution problem=
>=20=20
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20
>              2010/02/02 15:46=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20
>              Veuillez r=E9pondre=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20
>                      =E0=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20
>              s-news <at> lists.bios=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20
>                tat.wustl.edu=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=
>=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20=20
>
>
>
>
>I am sorry not being able to solve this simple problem by myself, but I
>would appreciate very much any help.
>
>I have a data frame with many variables and a lot of NA's dispersed around
>in the df.
>Now, I have to eksport the data frame for use in another program which
>cannot use the alfanumeric code 'NA', so I have to substitute an integer
>which then can be marked as 'missing' in the other program.
>
>But how do I substitute all NA's in the df with for instance the number '9'
>?
>
>Best,
>
>Jan Ivanouw PhD
>University of Copenhagen
>Denmark
>
>
>
>Le message ci-dessus, ainsi que les documents l'accompagnant, sont destin=
>=E9s
>uniquement aux personnes identifi=E9es et peuvent contenir des informations
>privil=E9gi=E9es, confidentielles ou ne pouvant =EAtre divulgu=E9es. Si vou=
>s avez
>re=E7u ce message par erreur, veuillez le d=E9truire.
>
>This communication ( and/or the attachments ) is intended for named
>recipients only and may contain privileged or confidential information
>which is not to be disclosed. If you received this communication by mistake
>please destroy all copies.
>
>
>
>
>Faites bonne impression et imprimez seulement au besoin !
>Think green before you print !
>
>Le message ci-dessus, ainsi que les documents l'accompagnant, sont destin=
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Doug Bolgiano | 4 Feb 19:20 2010

fitting same linear model to several response variables

I'm trying to develop a function in R for fitting a linear model with the same covariates to several response variables.  If the response variables, y1, y2, y3,...., yk are placed in a matrix, my (n x k), say, this can be can be done via the lm function,

             mfits <- lm(formula = my ~ x) 

mfits is a 'lm' object with components that are arrays rather than vectors.  When I make the same call from within a function (see below) it results in an error, apparently with the response matrix being seen as a list rather than a matrix.  Prior to the call to lm within the function, the response matrix is seen as matrix.  Can anyone offer insights as to why this error occurs and how to fix it? 

mlfit <- function(dataf, xdx, ydx) {
   ##### fit single expl. var linear model to several response vars
    nobs <- dim(dataf)[1]; ncol <- length(ydx)
    ym <- matrix(dataf[,ydx], nobs, ncol)
    xcv <- dataf[,xdx]
    ## check that 'ym' is a matrix
    if(!is.matrix(ym)) stop("Response vars not formatted as a matrix!!!")
    ## print the dimensions of the response matrix
    print(dim(ym))
    dimnames(ym)[[2]] <- names(dataf[ydx])
    ## print the response variable names
    print(dimnames(ym) [[2]] )
    mft <- lm(formula = ym ~ xcv)
    return(mft)
}

A call to the function mlfit gives the following result:

> try.mlf <- mlfit(bRdC, xdx = 7, ydx = 1:5)
[1] 25  5
[1] "WT"    "Q628A" "N633A" "K660A" "L664A"
Error in model.frame.default(formula = ym ~ xcv, drop.unused.levels = TRUE) :
  invalid type (list) for variable 'ym'

Thanks,
--
Doug Bolgiano  MS
Biostatistician
Research Division
Puget Sound Blood Center
Seattle, WA  98104

206 398-5982

Johannes Fuernkranz | 5 Feb 09:14 2010
Picon

ICML 2010 Call for Tutorial Proposals: Feb 13

ICML-2010 Call for Tutorials

The ICML-2010 Organizing Committee invites proposals for tutorials to
be held at the 27th International Conference on Machine Learning, on
Monday, June 21, 2010 in Haifa, Israel (http://www.icml2010.org).

We seek proposals for tutorials on core techniques and areas of
knowledge that enjoy broad interest within the machine learning
community. We are interested in tutorials on established or emerging
research topics within the field itself, but we also welcome tutorials
from related research fields or application areas provided that they
are of sufficient interest to the machine learning community. The
ideal tutorial should attract a wide audience. It should be broad
enough to provide a gentle introduction to the chosen research area,
but it should also cover the most important contributions in depth.
Proposals that exclusively focus on the presenters' own work or
commercial presentations are not eligible.

Guidelines for preparing a proposal can be found at:
http://www.icml2010.org/tutorials.html

Tutorial proposals should be submitted via email in PDF format to
tutorials <at> icml2010.org . Soon after submission, proposers should
expect to receive a verification of receipt.

The timeline is as follows:

  * Tutorial proposals due: February 13, 2010
  * Acceptance notification: February 28, 2010
  * Website due: March 15, 2010
  * Tutorial material due: May 30, 2010
  * Tutorials date: June 21, 2010

Contact: Ben Taskar
Tutorials Chair ICML 2010

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Gmane