'Ma model' diaporamas de présentation

Lepton flavour and neutrino mass aspects of the Ma-model

Lepton flavour and neutrino mass aspects of the Ma-model. Based on: Adulpravitchai, Lindner, AM: Confronting Flavour Symmetries and extended Scalar Sectors with Lepton Flavour Violation Bounds, Phys. Rev. D80 (2009) 055031

1.66k views • 149 slides

BCIC Meeting

BCIC Meeting. March 2014. Welcome. Introductions Overview of Agenda. SED Update. March 2014. SED Updates. Curriculum and Standards. Social Studies Frameworks draft April adoption likely Exam change 2018? 2019? Field Guide will be developed

668 views • 54 slides

13 Introduction toTime-Series Analysis

13 Introduction toTime-Series Analysis. What is in this Chapter?. This chapter discusses the basic time-series models: autoregressive (AR) and moving average (MA) models, stationary and nonstationary time series, and the Box-Jenkins approach to time-series modeling

817 views • 49 slides

13 Introduction toTime-Series Analysis

13 Introduction toTime-Series Analysis. What is in this Chapter?. This chapter discusses the basic time-series models: autoregressive (AR) and moving average (MA) models, stationary and nonstationary time series, and the Box-Jenkins approach to time-series modeling

646 views • 49 slides

Modeling methods

Modeling methods. Used in system identification and in MRAS. Linear in parameter models: (Models for describing linear systems). Auto-Regressive Model (AR model) Moving Average Model (MA model) Finite Impulse Response Model (FIR model)

675 views • 49 slides

Modeling methods

Modeling methods. Used in system identification and in MRAS. Linear in parameter models: (Models for describing linear systems). Auto-Regressive Model (AR model) Moving Average Model (MA model) Finite Impulse Response Model (FIR model)

694 views • 49 slides

BABS 502

BABS 502. ARIMA Forecasting March 18, 2014. General Overview. An ARIMA model is a mathematical model for time series data. Statisticians George Box and Gwilym Jenkins developed a systematic approach for fitting these models to data so these models are often called Box-Jenkins models.

514 views • 29 slides

Time Series Analysis of Nutrients on the Lower Mississippi River

Time Series Analysis of Nutrients on the Lower Mississippi River. 29 September 2004 @ Northeastern U. 41% of Continental US Heavily Farmed Regions(N) 56% of N from 5 states. http://www.epa.gov. Hypoxia. First noticed in 1972 Regular checking since 1985 1 Million Metric Tons Nitrate/year.

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BABS 502

BABS 502. ARIMA Forecasting Lecture 7 and 8 - March 14-16, 2011. General Overview. An ARIMA model is a mathematical model for time series data. George Box and Gwilym Jenkins developed a systematic approach for fitting these models to data so these models are often called Box-Jenkins models.

475 views • 27 slides

Functional Brain Signal Processing: EEG & fMRI Lesson 5

M.Tech. (CS), Semester III, Course B50. Functional Brain Signal Processing: EEG & fMRI Lesson 5. Kaushik Majumdar Indian Statistical Institute Bangalore Center kmajumdar@isibang.ac.in.

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Context-aware mobile application model and determination of its role in information systems

Context-aware mobile application model and determination of its role in information systems. Rok Rupnik, Ph.D. University of Ljubljana Faculty of Computer and Information Science. Overview. Information Socitey and Mobile Applications (MA) Mobile Device and MA

416 views • 26 slides

Seasonal Models

Seasonal Models. Materials for this lecture Lecture 3 Seasonal Analysis.XLS Read Chapter 15 pages 8-18 Read Chapter 16 Section 14. Uses for Seasonal Models. Have you noticed a difference in prices from one season to another? Tomatoes, avocados, grapes Wheat, corn, 450-550 pound Steers

350 views • 22 slides

The Global Impacts of Land Degradation: Final Report and Peer Review

The Global Impacts of Land Degradation: Final Report and Peer Review . Michael Stocking Vice-Chair, STAP-GEF International Workshop GEF Land Degradation Focal Area Indicators FAO, Rome 8 January 2007. Purpose.

326 views • 20 slides

Lecture 10 Time Series Model

Lecture 10 Time Series Model. Outline. Time series models Linear Time Series Models Moving Average Model Auto-regressive Model ARMA model Nonlinear Time Series Estimation Applications. What is a time series ? A scalar or vector-valued function of time indices Examples:

468 views • 15 slides

Model selection/diagnostics

231 views • 11 slides

LECTURE 12: PARAMETRIC AND MINIMUM VARIANCE SPECTRAL ESTIMATION. Objectives: AR Spectral Estimation MA Spectral Estimation ARMA Spectral Estimation Minimum Variance Estimation

114 views • 11 slides