'Multiple time series' diaporamas de présentation

Designing with the User in mind

Designing with the User in mind. Jamie Starke. Sizing the Horizon: The Effects of Chart Size and Layering on the Graphical Perception of Time Series Visualizations J. Heer , N. Kong, M. Agrawala (2009). CI 2009 Rethinking Visualization: A High-Level Taxonomy

913 views • 83 slides

Financial Market Integration

Financial Market Integration. ECB Notes, October 2004 Geert Bekaert Columbia University. FMI: What it is and what it is not. Financial market integration: situation where securities of similar risk command the same expected return => for most securities: joint test problem

737 views • 55 slides

Visualisation 2012 - 2013 Lecture 3

Visualisation 2012 - 2013 Lecture 3. Visualising Trends. Brian Mac Namee Dublin institute of Technology Applied Intelligence Research Centre. Origins. This course is based heavily on a course developed by Colman McMahon ( www.colmanmcmahon.com )

573 views • 51 slides

Environmental Data Analysis with MatLab

Environmental Data Analysis with MatLab. Lecture 18: Cross-correlation. SYLLABUS.

1.01k views • 46 slides

VAR Models

1.17k views • 32 slides

VAR Models

657 views • 32 slides

Tools for quantifying changes in ecosystem service delivery through time

406 views • 29 slides

NURS 2210-Roles II

NURS 2210-Roles II. Unit 1: Role of the RN in the Health Care System Nancy Pares, RN, MSN. Levels of education. Cert. Nurse Assistant, Med Aide LPN; LPN-C ASN BSN MSN; APRN PhD Specialists: Wound Care, Ostomy , Care Management, Diabetes,. Roles/Functions. Direct care provider

374 views • 24 slides

Chapter Seven

Chapter Seven. Causal Research Design: Experimentation. Concept of Causality. A statement such as " X causes Y " will have the following meaning to an ordinary person and to a scientist. ____________________________________________________ Ordinary Meaning Scientific Meaning

347 views • 21 slides

Automatic Speech Attribute Transcription (ASAT)

205 views • 10 slides

CHAPTER 14

CHAPTER 14. COINTEGRATION AND ERROR CORRECTION MODELS. COINTEGRATION. There is a unique case where a regression of a nonstationary series on another nonstationary series does not result in spurious regression. This is the situation of cointegration .

322 views • 5 slides

CHAPTER 14

CHAPTER 14. COINTEGRATION AND ERROR CORRECTION MODELS. COINTEGRATION. There is a unique case where a regression of a nonstationary series on another nonstationary series does not result in spurious regression. This is the situation of cointegration .

54 views • 5 slides

CHAPTER 14

CHAPTER 14. COINTEGRATION AND ERROR CORRECTION MODELS. COINTEGRATION. There is a unique case where a regression of a nonstationary series on another nonstationary series does not result in spurious regression. This is the situation of cointegration .

57 views • 5 slides