Random Error Propagation

Slides:



Advertisements
Similar presentations
1er. Escuela Red ProTIC - Tandil, de Abril, 2006 Principal component analysis (PCA) is a technique that is useful for the compression and classification.
Advertisements

Basic geostatistics Austin Troy.
Uncertainty Representation. Gaussian Distribution variance Standard deviation.
ARCGICE WP 2.2 ERROR ESTIMATION OF NEW GEOID C.C.Tscherning, University of Copenhagen,
Rotation of Coordinate Systems A x z y x* z* y* Rotation Matrix.
Time series analysis - lecture 5
Mobile Intelligent Systems 2004 Course Responsibility: Ola Bengtsson.
Adjustment theory / least squares adjustment Tutorial at IWAA2010 / examples Markus Schlösser adjustment theory Hamburg,
Lecture 15 Today Transformations between coordinate systems 1.Cartesian to cylindrical transformations 2.Cartesian to spherical transformations.
7. Least squares 7.1 Method of least squares K. Desch – Statistical methods of data analysis SS10 Another important method to estimate parameters Connection.
Generation & Propagation of Uncertainty Analysis P M V Subbarao Professor Mechanical Engineering Department A Measure of Confidence Level in compound Experiments…..
Algorithm Evaluation and Error Analysis class 7 Multiple View Geometry Comp Marc Pollefeys.
Empirical Financial Economics 2. The Efficient Markets Hypothesis - Generalized Method of Moments Stephen Brown NYU Stern School of Business UNSW PhD Seminar,
Modern Navigation Thomas Herring
Principles of Least Squares
Weights of Observations
1 5. Combination of random variables Understand why we need bottoms-up approach for reliability analysis Learn how to compute the probability density function,
1 SVY207: Lecture 18 Network Solutions Given many GPS solutions for vectors between pairs of observed stations Compute a unique network solution (for many.
Chapter 15 Modeling of Data. Statistics of Data Mean (or average): Variance: Median: a value x j such that half of the data are bigger than it, and half.
Geo479/579: Geostatistics Ch12. Ordinary Kriging (1)
Chapter 12 Multiple Linear Regression Doing it with more variables! More is better. Chapter 12A.
Chapter 6 BEST Linear Unbiased Estimator (BLUE)
Modern Navigation Thomas Herring
Chapter 7 Sampling and Sampling Distributions ©. Simple Random Sample simple random sample Suppose that we want to select a sample of n objects from a.
8 Sampling Distribution of the Mean Chapter8 p Sampling Distributions Population mean and standard deviation,  and   unknown Maximal Likelihood.
Colorado Center for Astrodynamics Research The University of Colorado 1 STATISTICAL ORBIT DETERMINATION ASEN 5070 LECTURE 11 9/16,18/09.
Modern Navigation Thomas Herring MW 11:00-12:30 Room
How Errors Propagate Error in a Series Errors in a Sum Error in Redundant Measurement.
Colorado Center for Astrodynamics Research The University of Colorado 1 STATISTICAL ORBIT DETERMINATION The Minimum Variance Estimate ASEN 5070 LECTURE.
Pg 1 of 10 AGI Sherman’s Theorem Fundamental Technology for ODTK Jim Wright.
Creating a Residual Plot and Investigating the Correlation Coefficient.
Ch14: Linear Least Squares 14.1: INTRO: Fitting a pth-order polynomial will require finding (p+1) coefficients from the data. Thus, a straight line (p=1)
Geology 6600/7600 Signal Analysis 02 Sep 2015 © A.R. Lowry 2015 Last time: Signal Analysis is a set of tools used to extract information from sequences.
1 Optimal design which are efficient for lack of fit tests Frank Miller, AstraZeneca, Södertälje, Sweden Joint work with Wolfgang Bischoff, Catholic University.
CHAPTER- 3.2 ERROR ANALYSIS. 3.3 SPECIFIC ERROR FORMULAS  The expressions of Equations (3.13) and (3.14) were derived for the general relationship of.
Objectives: Normal Random Variables Support Regions Whitening Transformations Resources: DHS – Chap. 2 (Part 2) K.F. – Intro to PR X. Z. – PR Course S.B.
Learning Theory Reza Shadmehr Distribution of the ML estimates of model parameters Signal dependent noise models.
COMP322/S2000/L111 Inverse Kinematics Given the tool configuration (orientation R w and position p w ) in the world coordinate within the work envelope,
Environmental Data Analysis with MatLab 2 nd Edition Lecture 22: Linear Approximations and Non Linear Least Squares.
The Coordinate Plane Mr. Thiel.
Computing the Values of Trig Functions of Acute Angles
Sampling and Sampling Distributions
LENGTH and PERIMETER.
Uncertainty and Error Propagation
Adjustment of Trilateration
LECTURE 06: MAXIMUM LIKELIHOOD ESTIMATION
STATISTICAL ORBIT DETERMINATION Coordinate Systems and Time Kalman Filtering ASEN 5070 LECTURE 21 10/16/09.
LECTURE 11: Advanced Discriminant Analysis
Multiple Imputation using SOLAS for Missing Data Analysis
Types of Research Designs
9.3 Filtered delay embeddings
CH 5: Multivariate Methods
Spectral Clustering.
Slope of the regression line:
Precisions of Adjusted Quantities
Lecture 25 Radial Basis Network (II)
Today (1/19/15) Learning objectives:
We have started to compute the traverse station
Today (1/21/15) Learning objectives:
The regression model in matrix form
PCA is “an orthogonal linear transformation that transfers the data to a new coordinate system such that the greatest variance by any projection of the.
Finding the Distance Between Two Points.
Regression Lecture-5 Additional chapters of mathematics
Revise No. 1.
Random Error Propagation
Uncertainty and Error Propagation
Propagation of Error Berlin Chen
Topic 11: Matrix Approach to Linear Regression
Survey Networks Theory, Design and Testing
Propagation of Error Berlin Chen
Presentation transcript:

Random Error Propagation

Errors in Indirect Quantities Thus far, we have worked with errors in direct measurements Often, we compute other quantities based on our direct measurements (e.g. angles and distances for traverse coordinates) By the method of error propagation, we can assess the impact of the measurements on the computed quantities

Rectangle Example Area of 100x40 rectangle is 4000. A one unit error gives an area of 101x41=4141. The error in area is 141, which is approximately 100x1 + 40x1.

Error Propagation Derivation

Cut to the Chase or Note the variance and covariance terms

In Matrix Form The covariance term shows the interdependence between unknowns. (Covariance matrix is symmetric)

General Matrix Form

For Independent Observations

SLOPOV For Nonlinear Functions

Example – Cylindrical Tank

Horizontal Distance Example