Human activity sensor data contains observations derived from sensor measurements taken from smartphones worn by people while doing different activities (walking, lying, sitting etc).

This example was authored by the MathWorks community.

Rare events prediction in complex technical systems has been very interesting and critical issue for many industrial and commercial fields due to huge increase of sensors and rapid growth

Demonstration of dot product, orthogonality also includes some vector addition. Information from this tutorial is used in qr decomposition and multiple regression regression approach

This example was authored by the MathWorks community.

This case study analyzes the amount of vibration a passenger experiences for a vehicle traveling over a road disturbance (bump). We want to determine the amount of reduction in displacement

Though Hotelling’s T-square method is applicable for many multi-dimensional data sets, this method has a fundamental assumption that the data follow a unimodal distribution. So, when the

This demo showcases visualization and analysis for forecasting energy demand based on historical data. We have access to hour-by-hour utility usage for the year 2006, including

Among many statistical anomaly detection techniques, Hotelling’s T-square method, a multivariate statistical analysis technique, has been one of the most typical method. This method

The dynamic response of a 100 m high clamped-free steel beam is studied. Simulated time series are used, where the first three eigenmodes have been taken into account. More precisely, the

This tutorial describes multivariate guassians as it walks through the major functioniality of the mmvn toolkit

The previous methods, Hotelling’s T-square method and Gaussian mixture model, use Gaussian distribution-based parametric model. However, in practical situation, sometimes data

Hypothesis testing based on a model that is invalid can lead to faulty conclusions. this tutorial goes over a few basic diagnostic procedures that can be used to test whether a model is valid.

Linstats package provides a uniform mechanism for building any supported linear model. Once built the same model can be analyzed in many ways including least-squares regression, fit and

After Cross-Validation, Optimal 'c' value- Yeilding Best Performance (F-measure)

From: "Using Statistics and Optimization to Support Design Activities" Webinar, July 21, 2009.

This tutorial will go over some of the functions available for making inferences and testing hypothesis. I assume that you know how to construct a model using encode. If not see the

This example was authored by the MathWorks community.

This example was authored by the MathWorks community.

This example was authored by the MathWorks community.

After Cross-Validation, Optimal 'c' value- Yeilding Best Performance (F-measure)

Bhartendu, Machine Learning & Computing, Mathworks File Exchange

The time series from a SDOF is computed using the central difference method, and a white noise is used as an input force.

| AdaBoost : Implemented in 2-dimensional projection space. (i.e.Number of Pricipal Components = 2) |

In order to illustrate some of the numerical calculations required for testing hypothesis on canonical variance components based on the LRT statistic (37), as presented in Example 3, let us

Q = 1*Q_1 + 2*Q_1 + 3*Q_5 For chi2 distribution use the NEGATIVE (!) sign for degrees of freedom

Overview

In this script, I reproduce the results presented by John D. Holmes in the first part of the chapter 2 of his book: Wind loading of structures [1]. The notations he uses are slightly different in

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Overview

This is an enhanced version of the regstats function (statistics toolbox). Here are implemented several ways to estimate robust standard errors (se) for the coefficients\n. Also, it

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Choosen Weak classifiers:

Copyright (c) 2016, The MathWorks, Inc.

This file describes the development of a failure boundary identication algorithm shown in "Using Statistics and Optimization to Support Design Activities" Webinar, July 21, 2009.

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This HighChart object enables easy use of the javascript technology provided by http://www.highcharts.com/ to generate interactive and dynamic charts in MATLAB web browser.

The Cox-Ingersoll-Ross process

The state of Connecticut collects data on repairs performed to their fleet of vehicles. The data can be accessed here: https://catalog.data.gov/dataset/vehicle-repairs

コネチカット州では、車の修理時のデータを収集しています。

多変数の時系列データを複数使用します。それぞれの時系列データはそれぞれ同じ型ですが、別々のエンジンで計測しされたものです。 通常エンジンにはユーザーにはわからない様々なレベルの摩耗、製造変動が初期段階から存在しますが、故障しているわけではありません。

This example was authored by the MathWorks community.

This example was authored by the MathWorks community.

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(日本語テキストを対象とした解析)

Bhartendu, Machine Learning & Computing, Mathworks File Exchange

Examples A and B make it clear that if we are trying to view uniform data over the hypercube most (spherical) neighborhoods will be empty! Let us examine what happens if the data follow the

To support the port passing problem I'll need to derive some recurrence equations that allow us to talk about the expected number of steps given that we win Gambler's Ruin (rather than lose).

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Pi day is coming and you have been invited to dine with an eccentric but mathematically minded host. She has provided many interesting delicacies and you have now finally arrived at the cheese

From WinningGamblersRuin.mlx we know that

Consider the hypercube and an inscribed hypersphere with radius . Then the fraction of the volume of the cube contained in the hypersphere is given by:

Consider 2 spheres centered on the origin, one with radius and the other with slightly smaller radius . The volume of a -dimensional hypershere with radius is given by:

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From WinningGamblersRuin.mlx we know that

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For a table size of 3 it is fairly simple to enumerate all possible paths and their probabilities. So to deduce the expected path length all we need to do is sum over all the paths. Looking first at

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Copyright (c) 2016, The MathWorks, Inc.

故障が発生した場合の損失が甚大である場合、保守的なスケジュールで（より短い期間で）メンテナンスを行うことで、故障の発生を避けるアプローチはよく取られます。 ただこのアプローチでは結果として必要以上にメンテナンスを実施することに繋がることが多く、余計なコストとなります。

We are trying to extend the case where a Markov Chain representing Gambler's Ruin contains one boundary that does not adsorb the chain, but instead reflects it. This can be represented with

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