Gaussian statistics - PowerPoint PPT Presentation

The Secretariat of the Task Team on International Trade Statistics, under the United Nations Committee of Experts on Business and Trade Statistics, is actively involved in revising manuals on international trade statistics. Established in 2021, the team focuses on enhancing the integration between t

4 views • 28 slides

Learn about the core concepts of statistics in business through this MSMSR lecture plan module covering topics such as the introduction to statistics, definition of statistics, functions, scope, limitations of data, classification of data, and tabulation of data. Discover how statistics plays a cruc

2 views • 37 slides

Explore the dangers of relying on the Gaussian copula model for pricing risks in the financial world, leading to the catastrophic collapse of 2008. Discover how the lure of profits overshadowed warnings about the model's limitations, causing trillions of dollars in losses and threatening the global

7 views • 18 slides

Gaussian Elimination and Gauss-Jordan Elimination are methods used in linear algebra to transform matrices into reduced row echelon form. Wilhelm Jordan and Clasen independently described Gauss-Jordan elimination in 1887. The process involves converting equations into augmented matrices, performing

4 views • 14 slides

This insightful content dives into the Gaussian Distribution, including its formulation for multidimensional vectors, properties, conditional laws, and examples. Explore topics like Mahalanobis distance, covariance matrix, elliptical surfaces, and the Gaussian distribution as a Gaussian function. Di

0 views • 19 slides

Exploring Sparse Linear Solvers and Gaussian Elimination methods in solving systems of linear equations, emphasizing strategies, numerical stability considerations, and the unique approach of Sparse Gaussian Elimination. Topics include iterative and direct methods, factorization, matrix-vector multi

0 views • 35 slides

Gaussian Elimination is a powerful method used to solve systems of linear equations. It involves transforming augmented matrices through row operations to simplify and find solutions. Homogeneous linear systems have consistent solutions, including the trivial solution. This method is essential in li

0 views • 16 slides

The development of quantum statistics plays a crucial role in understanding systems with a large number of identical particles. Symmetric and anti-symmetric wave functions are key concepts in quantum statistics, leading to the formulation of Bose-Einstein Statistics for bosons and Fermi-Dirac Statis

1 views • 15 slides

Mr. Phetsavanh BOUTLASY, Chief of Registration Statistics Division at the Lao Statistics Bureau, discusses the legislative framework, national statistics system development strategy, challenges faced in vital statistics, and plans to enhance statistical production. The strategy aims for sustainable

0 views • 11 slides

The UK Statistics Authority, established under the Statistics and Registration Service Act 2007, plays a crucial role in promoting the production and publication of high-quality official statistics in the field of health and care. They emphasize the importance of trustworthy, valuable statistics tha

0 views • 9 slides

This paper proposes a method for dimensionality reduction based on functional approximation using Gaussian basis functions. Nonlinear Gauss weights are utilized to train a least squares support vector machine (LS-SVM) model, with further variable selection using forward-backward methodology. The met

0 views • 23 slides

Explore Gaussian statistics in population sampling scenarios, understanding Z-based limit testing and confidence intervals. Learn about statistical tests such as F-tests and t-tests through practical examples like fish weight and cholesterol level measurements. Master the calculation of confidence i

0 views • 8 slides

This work discusses fast high-dimensional filtering techniques in Fully-Connected Conditional Random Fields (CRF) through methods like Gaussian filtering, bilateral filtering, and the use of permutohedral lattice. It explores efficient inference in CRFs with Gaussian edge potentials and accelerated

0 views • 25 slides

This comprehensive pipeline includes processes for stellar kinematics, continuum fitting, Gaussian line fitting, and analysis of SAMI-like cubes. It also covers Gaussian fitting techniques, parameter mapping, and potential issues. The pipeline features detailed steps and strategies for accurate anal

0 views • 10 slides

Robot localization in a hallway is achieved through Kalman-like filters that use sensor data to estimate the robot's position based on a map of the environment. This process involves incorporating measurements, updating state estimates, and relying on Gaussian assumptions for accuracy. The robot's u

1 views • 26 slides

Exploring the connections between binomial, Poisson, and Gaussian distributions, this material delves into probabilities, change of variables, and cumulative distribution functions within the context of experimental methods in nuclear, particle, and astro physics. Gain insights into key concepts, su

0 views • 13 slides

This information pertains to the vital statistics questionnaire and response rates discussed during the Third Regional Workshop on Production and Use of Vital Statistics in 2014 in Daejeon, Republic of Korea. It covers the collection of vital statistics related to fertility, general mortality, infan

0 views • 13 slides

Gaussian Processes (GP) are explored for treating model defects in nuclear data evaluations. The presentation discusses the impact of model defects on evaluation results and proposes using GP to address these issues. The concept of GP and its application in treating model defects are detailed, highl

2 views • 28 slides

Uppsala University is investing efforts in developing the TENDL methodology to incorporate model defect methods for nuclear data evaluations. By leveraging Gaussian Processes and Levenberg-Marquardt algorithm, they aim to improve the accuracy and reliability of calibration data to produce justified

0 views • 16 slides

The presentation delves into the MIK estimator, exploring its impact on estimation with constant class means and non-Gaussian data. Review of initial results, examination of class mean bias in upper tail, and implications for metal containment are discussed. Cross-validation study findings, future w

0 views • 9 slides

In the realm of quantum statistics, various ensembles such as the grand canonical ensemble play a crucial role in describing the behavior of systems like gases and biological molecules. Understanding concepts such as Gibbs factor, chemical potential, and the probabilities of states being occupied sh

1 views • 19 slides

Bayesian optimization is being used at LCLS to tune the Free Electron Laser (FEL) pulse energy efficiently. The current approach involves a tradeoff between human optimization and numerical optimization methods, with Gaussian processes providing a probabilistic model for tuning strategies. Prior mea

1 views • 16 slides

Gaussian Processes (GPs) have wide applications in statistics and machine learning, encompassing regression, spatial interpolation, uncertainty quantification, and more. This content delves into the nature of GPs, their use in different communities, modeling mean and covariance, as well as the nuanc

0 views • 50 slides

In the field of reservoir modeling, Gaussian mixture models offer a powerful approach to estimating rock properties such as porosity, sand/clay content, and saturations using seismic data. This analytical solution of the Bayesian linear inverse problem provides insights into modeling reservoir prope

0 views • 10 slides

Thematic Enterprise Statistics division headed by Joe Madden at the Central Statistics Office in Ireland covers various aspects including Access to Finance, Energy Statistics, Financial Sector Data, Foreign Affiliates Statistics, ICT Enterprise Figures, Innovation and R&D Statistics, Outsourcing Dat

1 views • 21 slides

Gene sets in various downstream analyses such as disease signature identification, drug pathway association, survival analysis, and drug response prediction come from diverse sources and play a crucial role in boosting the signal-to-noise ratio. Gaussian embedding is utilized to model uncertainty, p

0 views • 14 slides

Intricacies of nonsymmetric Gaussian elimination, LU factorization, partial pivoting, left-looking column LU factorization, symbolic sparse Gaussian elimination, column preordering for sparsity, and more in numerical linear algebra algorithms.

0 views • 28 slides

Bayesian inference, Metropolis-Hastings, Hamiltonian Monte Carlo, and Markov Chain Monte Carlo are explored in the context of sampling techniques and estimation of probability distributions in complex models. The use of Gaussian processes to enhance the efficiency of Hamiltonian Monte Carlo is discu

0 views • 14 slides

Energy eigenvalues and eigenfunctions in quantum mechanics are studied through the exact solution of the radial Schrödinger equation for Gaussian potentials, using the Asymptotic Iteration Method. The method's efficiency in solving wave equations for different potentials is highlighted, with a focu

0 views • 23 slides

In Chapter 4, the method of least squares for estimating the mean in Gaussian distribution is discussed using the method of maximum likelihood. The concept is explained through equations detailing the probability function and calculation of the most probable value for the mean.

0 views • 9 slides

This project focuses on developing a robot-assisted steady ultrasound imaging system using deep learning techniques. The aim is to address challenges in imaging real tissue with non-random scatterer configurations, where traditional models may fall short. By employing Gaussian Process and motion est

0 views • 21 slides

Explore the world of analogue communication with a focus on thermal noise and additive white Gaussian noise in this lecture series by Dr. Haider Tarish Haider at the University of Mustansiriyah. Dive into the fundamentals of communication theory with informative slides and engage in a Q&A session fo

0 views • 10 slides

Explore the concepts of sparse linear solvers, including strategies for solving systems of linear equations with many zeros, the distinction between direct and iterative methods, and an overview of Gaussian Elimination for numerical stability. Gain insights into the algorithms, techniques, and consi

0 views • 35 slides

Understand Gaussian process emulators for multiple outputs, including simulators, GP modeling, mean functions, and covariance functions. Learn how to validate and optimize the emulator effectively.

0 views • 17 slides

Learn about Gaussian processes and their use in nonparametric regression, exploring concepts like multivariate normal distributions, covariance matrices, and Bayesian parameter estimation. Gain insights into the advantages and applications of Gaussian distributions in modeling complex data.

0 views • 30 slides

Explore the concepts of Gaussian Mixture Model (GMM) and Expectation Maximization (EM) through recitation slides covering motivation, formulation, definitions, and detailed steps of EM algorithm. Understand how GMM works as a distribution and dive into the intricacies of EM for inference and learnin

0 views • 14 slides

Explore paraxial analysis of Gaussian beams using OSLO software for optical layout in laser systems. Learn theory, system setup, beam tracing, and more. Extensive capabilities beyond basics covered in this tutorial. Images and step-by-step instructions included.

0 views • 16 slides

Explore the concept of Independent Component Analysis (ICA) in this informative project presentation. Learn about the Cocktail Party Problem, ICA model, Fast ICA algorithm, and more. Discover the motivation behind ICA and the process of estimating original speech signals. Understand the principles a

0 views • 23 slides

Explore the role of covariance functions in Gaussian processes for active machine learning and agency applications. Understand how kernel functions create covariance matrices, influencing the distribution of function values. Learn about smoothness assumptions, signal variance, noise variance, and mo

0 views • 49 slides

Explore the optimization of a GPU-accelerated Gaussian filter implementation for image processing, focusing on library usage, preprocessing strategies, GPU kernel design, timing results, and proposed improvements for enhanced performance.

0 views • 10 slides