Search for tag: "estimator"

Sara Wade & Karla Monterrubio-Gomez (Edinburgh): On MCMC for variationally sparse Gaussian processes: A pseudo-marginal approach.

The subtitles/captions on this talk are being edited. They will be available within 2 weeks of the talk being published. 26 February 2021Sara Wade & Karla Monterrubio-Gomez (Edinburgh): On MCMC…

From  OLLIE Quinn on March 1st, 2021 0 likes 3 plays 0  

Michael Feischl 8 February 2021 Black box algorithms for adaptive FEM

An automated programme has been used to generate the subtitles on this talk.

From  OLLIE Quinn on February 8th, 2021 0 likes 49 plays 0  

FDS-S2-03-1-3 Large sample theory of A/B testing

We work through how to apply large-sample theory to A/B testing.

From  David Sterratt on January 28th, 2021 0 likes 122 plays 0  

FDS-S2-01-2-8 Interpretation of confidence intervals

We'll consider two aspects of the interpretation of confidence intervals

From  David Sterratt on January 15th, 2021 0 likes 119 plays 0  

FDS-S2-01-2-7 Bootstrap confidence intervals

We introduce the bootstrap method of estimating confidence intervals

From  David Sterratt on January 15th, 2021 0 likes 134 plays 0  

FDS-S2-01-2-6 Estimating the confidence interval of means of large samples

We'll derive confidence intervals for the mean of large samples, when we can assume the sampling distribution of the mean is normal.

From  David Sterratt on January 15th, 2021 0 likes 139 plays 0  

FDS-S2-01-2-5 Definition of confidence intervals

We give a formal definition of confidence intervals, and show how the random interval can be converted to a random variable

From  David Sterratt on January 15th, 2021 0 likes 138 plays 0  

FDS-S2-01-2-3 Standard error

We introduce the standard error of an estimator and, in particular, the standard error of the mean.

From  David Sterratt on January 14th, 2021 0 likes 162 plays 0  

FDS-S2-01-2-2 Bias and variance

We'll introduce the concept of bias and variance of estimators.

From  David Sterratt on January 14th, 2021 0 likes 173 plays 0  

FDS-S2-01-2-1 Introduction to estimation

We'll introduce the concept of estimating a population or distribution parameter from a sample.

From  David Sterratt on January 14th, 2021 0 likes 195 plays 0  

Topic 65: Time Averages and Ergodicity (PETARS, Chapter 8)

This Topic introduces the notion of estimating statistical averages from a single realisation of a stochastic process. This concept is most easily developed for estimating first and second moments…

From  James Hopgood on November 14th, 2020 0 likes 77 plays 0  

Topic 49: Least Squares Estimation (PETARS, Chapter 6)

The least squares approach is presented as a non-probabilistic method for designing an estimator of a set of parameters, assuming a model is provided for describing the data. This is presented as…

From  James Hopgood on October 28th, 2020 0 likes 63 plays 0  

Topic 48: Maximum Likelihood Estimation (PETARS, Chapter 6)

This video introduces the maximum likelihood estimator (MLE) technique as a way of determining a good estimator for a given probabilistic problem. This method is very straightforward and intuitive,…

From  James Hopgood on October 26th, 2020 0 likes 76 plays 0  

Topic 47: Cramer-Rao Lower Bound for Parameter Vectors (PETARS, Chapter 6)

In this video, the concepts in estimation theory introduced so far for scalar random variables are extended to deal with estimating multiple parameters, for example the mean and variance of a…

From  James Hopgood on October 26th, 2020 0 likes 77 plays 0  

Topic 46: Cramer-Rao Lower Bound (PETARS, Chapter 6)

In this video, the question of finding the lower bound on the performance of all estimators for a particular probabilistic problem, as a benchmark with which to compare the performance of a given…

From  James Hopgood on October 24th, 2020 0 likes 94 plays 0  

Topic 44: Minimum Mean Square Error Estimators (PETARS, Chapter 6)

This video introduces the simple mean square error (MSE) as a criterion which trades-off bias and variance for an estimator. The relationship between the MSE and bias and variance is defined. The…

From  James Hopgood on October 23rd, 2020 0 likes 75 plays 0