Presentation is loading. Please wait.

Presentation is loading. Please wait.

IP, IST, José Bioucas, 2007 1 Probability The mathematical language to quantify uncertainty  Observation mechanism:  Priors:  Parameters Role in inverse.

Similar presentations


Presentation on theme: "IP, IST, José Bioucas, 2007 1 Probability The mathematical language to quantify uncertainty  Observation mechanism:  Priors:  Parameters Role in inverse."— Presentation transcript:

1 IP, IST, José Bioucas, 2007 1 Probability The mathematical language to quantify uncertainty  Observation mechanism:  Priors:  Parameters Role in inverse problems

2 IP, IST, José Bioucas, 2007 2 Overview of Probability  Definition; Properties  Independency; Conditional probability; Bayes theorem  Random variables; Cumulative distribution function  Examples of random variables  Bivariate distributions; Marginal distribution;Conditional distribution  Multivariate distributions; Marginal distribution;Conditional distributions  Expectation of a random variable; Variance; Covariance  Conditional expectation of a random variable; Variance; Covariance  Weak law of large numbers Ref. Larry Wasserman, All of Statistics. A Concise Course in Statistical Inference, Springer, 2004

3 IP, IST, José Bioucas, 2007 3 Definition Frequencist interpretation: Number of occurencies of A Number of repetitions Bayesain interpretation: Measures an observer’s strength of belief that A is true In probability the interpretation does not matter sample space event

4 IP, IST, José Bioucas, 2007 4 Independency; Conditional probability    

5 IP, IST, José Bioucas, 2007 5 Random variables  

6 IP, IST, José Bioucas, 2007 6 Random variables   

7 IP, IST, José Bioucas, 2007 7 Some discrete random variables From Wikipedia

8 IP, IST, José Bioucas, 2007 8 Some discrete random variables From Wikipedia

9 IP, IST, José Bioucas, 2007 9 Some continuous random variables

10 IP, IST, José Bioucas, 2007 10 Some continuous random variables

11 IP, IST, José Bioucas, 2007 11 Some continuous random variables

12 IP, IST, José Bioucas, 2007 12 Bivariate distributions

13 IP, IST, José Bioucas, 2007 13 Bivariate distributions

14 IP, IST, José Bioucas, 2007 14 Bivariate distributions

15 IP, IST, José Bioucas, 2007 15 Expectation

16 IP, IST, José Bioucas, 2007 16 Expectation

17 IP, IST, José Bioucas, 2007 17 Expectation

18 IP, IST, José Bioucas, 2007 18 Expectation

19 IP, IST, José Bioucas, 2007 19 Expectation

20 IP, IST, José Bioucas, 2007 20 Expectation

21 IP, IST, José Bioucas, 2007 21 Expectation

22 IP, IST, José Bioucas, 2007 22 Multivariate Normal

23 IP, IST, José Bioucas, 2007 23 Multivariate Normal

24 IP, IST, José Bioucas, 2007 24 Inequalities

25 IP, IST, José Bioucas, 2007 25 Laws of large numbers

26 IP, IST, José Bioucas, 2007 26 Central Limit Theorem


Download ppt "IP, IST, José Bioucas, 2007 1 Probability The mathematical language to quantify uncertainty  Observation mechanism:  Priors:  Parameters Role in inverse."

Similar presentations


Ads by Google