Random Variation

"Things go wrong. The odds catch up. Probability is like gravity: you cannot negotiate with gravity." James 'Sonny' Crockett, Miami Vice The Movie.

Monday, June 30, 2025

What is a Kalman Filter?

 





Kalman Filter

Posted by G. W. Pasdirtz at 2:10 PM No comments:
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What is the Attractor Path?


 

Posted by G. W. Pasdirtz at 1:59 PM No comments:
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About Me

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G. W. Pasdirtz
I use my blogs to make informal comments on policy topics related to my research interests in the World-System, computer simulation of the US Health Care System, the US Economy, the US Stock Market, and the US Financial System. I am retired from the University of Wisconsin -- Madison. I have taught Statistics and Computer Science and also served on the UW's HIPAA Task Force and the Bioterrorism Task Force. I have also been a member of my local planning commission, a jazz guitarist and a golfer, so some of that may find its way into the blogs.
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Blog Archive

  • ▼  2025 (6)
    • ▼  June (3)
      • What is a Kalman Filter?
      • What is the Attractor Path?
      • What is a Shock Decomposition?
    • ►  April (2)
    • ►  February (1)
  • ►  2024 (1)
    • ►  December (1)
  • ►  2020 (1)
    • ►  December (1)
  • ►  2013 (1)
    • ►  September (1)
  • ►  2012 (13)
    • ►  December (4)
    • ►  October (1)
    • ►  September (3)
    • ►  March (1)
    • ►  February (1)
    • ►  January (3)
  • ►  2011 (4)
    • ►  December (3)
    • ►  November (1)

My Blog List

  • Statistical Modeling, Causal Inference, and Social Science
    Getting rid of the “scientist as hero” model without replacing it by the “someone else is hero” model
    11 hours ago
  • Facts, Fictions and Forecasts
    World-System (2000-2150) Seven Futures for Iran
    2 weeks ago
  • George Pasdirtz
    Why MAGA?
    2 months ago
  • Random Stock Walker
    Boiler Plate
    2 months ago
  • Stochastic Trend
    Top Economics Blogs
    3 months ago
  • Econometrics Beat: Dave Giles' Blog
    What is a Permutation Test?
    6 years ago
  • Causal Analysis in Theory and Practice
    Simpson’s Paradox: The riddle that would not die. (Comments on four recent papers)
    8 years ago
  • Data Analysis
    One-Way ANOVA Video
    12 years ago
  • Error Statistics Philosophy
    MOVED: Reflections on the Paradigm Change (2/1/12): NEW ADDRESS: http://errorstatistics.com
    13 years ago

Background Links

  • Akaike Information Criterion (AIC)
  • Analysis of Covariance
  • Attractor Theory
  • Backfitting algorithm
  • Bayes Factor
  • Bayes Information Criterion (BIC)
  • Bayes Rule
  • Bayesian Inference
  • Bayesian Network
  • Bayesian Network Theory
  • Bayesian Networks, Video
  • Bayesian Statistics
  • Berkson's paradox
  • BibTeX
  • BibTeX Document
  • BibTeX Project
  • Binomial Distribution
  • Bonferroni correction
  • Bootstrapping
  • By-Group Processing in R
  • Causality
  • Central Limit Theorem (CLT)
  • Chain Rule (probability)
  • Chaos Theory
  • Chi-squared distribution
  • Cholesky decomposition
  • Classical Hypothesis Testing
  • Clinical trial
  • Cointegration
  • Conditional distribution
  • Conditional probability
  • Confidence Interval
  • Confounding
  • Counterfactual Conditionals
  • Covariance Matrix
  • Covariate
  • Credible Interval
  • Critical experiment
  • Cronbach's Alpha
  • Cross-validation
  • Cumulative Distribution Function (CDF)
  • d-separation
  • Density Estimation
  • Dependent and independent variables
  • Design of experiments
  • Deviance (statistics)
  • Deviance Information Criterion (DIC)
  • Directed Acyclic Graphs (DAGs)
  • Directed graph
  • DIscriminant Analysis
  • DOT graphics language
  • DOT tutorial and specification
  • dse (Dynamic System Estimation) package
  • Dynamic causal modelling
  • Ecological correlation
  • Effect size
  • Eigenvalue decomposition
  • EM Algorithm
  • Empirical Bayes Method
  • Empirical cumulative distribution function
  • Error function
  • Errors-in-variables Models
  • Examples.R
  • Expected value
  • Exploratory data analysis
  • F-distribution
  • Final Predictor Error (FPE) Test
  • Fisher's z-transformation
  • Focused Information Criterion (FIC)
  • Frequentist Inference
  • General Linear Model (GLM)
  • Generalized chi-squared distribution
  • Generalized Cross Validation (GCV) Statistic
  • Generalized Least Squares
  • Generalized Linear Model
  • Goodness of Fit
  • Granger causality
  • Graphviz: Open Source Graph Visualization
  • Hannan-Quinn Information Criterion (HQC)
  • Hierarchical (Nested) Data Structures
  • Hierarchical Linear Models
  • HLM package
  • hlmmc manual
  • hlmmc package
  • HLMprocedures.R
  • Homogeneity of Variance
  • Hypothesis
  • Identifiability
  • Ignorability
  • Importance sampling
  • Incidence Graphs
  • Instrumental variable
  • Interval Estimation
  • Introduction to R (pdf)
  • Inverse Distribution Function (Quantile Function)
  • Inverse transform sampling
  • Iteratively Reweighted Least Squares
  • Jackknife
  • Jensen-Shannon Divergence (JSD)
  • Jerzy Neyman
  • Joint distribution
  • Joint probability
  • Judea Pearl
  • Karl Pearson
  • Karl Wuensch's Statistics Lessons
  • Kernel density estimation
  • Kernel smother
  • Kullback-Leibler Divergence (KLD)
  • Lack-of-fit sum of squares
  • Latent Class Models
  • Latent Growth Modeling
  • Latent Variable Model
  • LaTeX
  • LaTeX Documentation
  • LaTeX Project
  • Least Squares
  • Levene's Test
  • Lexical Scope in Programming Languages
  • LibraryLoad.R
  • Likelihood function
  • Likelihood Intervals
  • Likelihood-ratio test
  • Linear Algebra in R
  • Linear Regression
  • LISREL
  • lme4 package
  • Lyapunov stability
  • Marginal distribution
  • Markov Chain
  • Markov Chain (Random Walk) Monte Carlo
  • Markovian (Markov process)
  • Matrix Theory
  • Maximum Likelihood
  • MCMC (Markov Chain Monte Carlo)
  • Mean squared error
  • Mediation (statistics)
  • Meta-analysis
  • Minimum Message Length (MML) Test
  • Mixed Models
  • Model Selection
  • Monte Carlo Methods
  • Multicollinearity
  • Multilevel Model
  • Multinomial Distribution
  • Multivariate analysis of variance (MANOVA)
  • Multivariate Normal Distribution
  • Multivariate Statistics
  • Mutual exclusion
  • Neyman construction
  • Neyman-Pearson lemma
  • Non-parametric Statistics
  • Noncentral chi-squared distribution
  • Normal Distribution
  • Object-oriented Programming (OOP)
  • Occam's Razor
  • OpenMX
  • P-value
  • Parameter identification
  • Parametric Statistics
  • Path Analysis
  • Path Coefficient
  • Pooled Variance
  • Portmanteau Test
  • Post-hoc analysis
  • Posterior probability
  • Power-law probability distributions
  • Prediction Interval
  • Principal Component Analysis
  • Probability
  • Probability distribution function (PDF)
  • Probability integral transformation
  • Probability theory
  • Quantile
  • Quantile function
  • Quasi-experimental Design
  • Quick-R Stat Methods
  • R Graphics
  • R Programming
  • R programming language
  • R Programming WikiBook
  • R-project for Statistical Computing
  • R-squared (coefficient of determination)
  • Random effects model
  • Random Sampling
  • Random Walk
  • Random Walk Hypothesis
  • Rank Transformation
  • Reality Check bootstrap
  • Regression analysis
  • Rejection Sampling
  • Reliability
  • Repeated Measures
  • Resampling Statistics
  • Restricted Maximum Likelihood (REML)
  • Rice Criterion Test
  • Robust Confidence Intervals
  • Ronald Fisher
  • Rubin causal model (RCM)
  • S programming language
  • Scheme programming language
  • Scientific Hypothesis
  • Scientific Theory
  • SEM (Structural Equation Modeling)
  • Singular Value Decomposition (SVD)
  • Smalltalk
  • Spline interpolation
  • Standard deviation
  • Standard error
  • Statistical Hypothesis testing
  • Statistical Inference
  • Statistical Power Analysis
  • Stratified sampling
  • Structural Equation Model (SEM)
  • Student's t-distribution
  • Student's t-test
  • Sweave
  • Sweave Users Manual
  • Sweave, creating documents
  • System identification
  • Tolerance Interval
  • Triangular distribution
  • Uniform distribution
  • Unit Root
  • Validity
  • Wald test
  • Wilk-Shapiro Test
  • William Sealy Gosset (Student)
  • Wishart distribution

Quotable

"The social aspect of science needs also to be recognized. Science is a group activity that relies heavily on mutual criticism to maximize the validity of conclusions. Much of what characterizes good research is the ability to anticipate, and neutralize with data, potential criticisms of conclusions" (Norman Cliff, 1983).

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