• ## R language structural equation model SEM multiple regression and model diagnosis analysis student test score data and visualization

Time：2022-8-2

Original link: http://tecdat.cn/?p=24694 This article first shows how to import data into R. Then, the correlation matrix is generated, and then the regression analysis of two predictive variables is carried out. Finally, it shows how to output the matrix as an external file and use it for regression. Data entry and cleaning First, we will […]

• ## Research on the popularity of teachers with extended tecdat|r language lme4 mixed effect model

Time：2022-7-15

Original link:http://tecdat.cn/?p=11724 Source of original text:Tuoduan data tribe official account introduce This tutorial is for multiple layers_ Regression_ The model is introduced. This tutorial expects: Multilayer_ Regression_ Basic knowledge of the model. Basic knowledge of coding in R. Install R packagelme4, andlmerTest。  Step 1: Set If you have not installed all the packages mentioned below, […]

• ## NF RESNET: remove BN normalization, network signal analysis worthy of careful reading | ICLR 2021

Time：2022-7-6

This paper proposes NF RESNET, which analyzes the actual signal transmission of the network, simulates the performance of batchnorm in the transmission of mean and variance, and then replaces batchnorm. The experiment and analysis of the paper are very sufficient, and the effect is also very good. The theoretical effect of some initialization methods is […]

• ## Extended tecdat|r language multivariate copula GARCH model time series prediction

Time：2022-7-5

Original link  http://tecdat.cn/?p=2623 Source of original text:Tuoduan data tribe official account Unlike macroeconomic data, financial markets are mostly high-frequency data, such as stock yield series. Intuitively speaking, the latter is a sequence with more “fluctuations” and random fluctuations than the former. In the case of univariate or multivariate, building copula function model and GARCH model is […]

• ## Extended tecdat|r language generalized additive model gams analyzes temperature and ozone environmental data, and draws partial regression diagram and partial residual diagram

Time：2022-7-2

Original link: http://tecdat.cn/?p=23697 We use r library mgcv and generalized additive models (gams) to model environmental data. Mgcv is a great library with rich functions, but we often find that the default diagnostic diagram is not exciting. In particular, the partial residual diagram has strong functions, but it is not beautiful, and the residual is […]

• ## Matlab uses empirical mode decomposition EMD to denoise signals

Time：2022-6-28

Original link : http://tecdat.cn/?p=2567 Original source:Tuoduan data tribe official account For this example, consider a nonstationary continuous signal consisting of sine waves with significant frequency variations. The vibration or fireworks sound of a jackhammer is an example of a nonstationary continuous signal. Loading nonstationary signal data at sampling frequencyfsAnd visualize the mixed sinusoidal signal. load（’sinusoidalSignalExampleData.mat’，’X’，’fs’）;    xlabel（’Time（s）’）; […]

• ## Extended tecdat|r language Econometrics: instrumental variable method (two-stage least square method 2SLS) linear model analysis of per capita food consumption time series data and regression diagnosis

Time：2022-6-21

Original link:http://tecdat.cn/?p=23759 Headline brief introduction The linear model of two-stage least squares (2SLS) regression fitting is a commonly used tool variable estimation method. The main content of this paper is to extend the regression diagnosis of various standards to 2SLS. Review of 2SLS estimation We need some basic results of 2SLS regression to develop a […]

• ## Machine learning algorithm series (V) – lasso regression algorithm

Time：2022-6-1

Background knowledge points required for reading this article: linear regression algorithm and yidudui programming knowledge 1、 Introduction    in the previous section, we learned that one method to solve multicollinearity is to regularize the cost function. One regularization algorithm is called ridge regression algorithm. Let’s learn another regularization algorithm-Lasso regression algorithm)1(lasso regression algorithm), the full […]

• ## Research on traffic casualty accident prediction based on extended tecdat|r language Markov transformation model

Time：2022-5-22

Original link:http://tecdat.cn/?p=12227 Original source:Tuoduan data tribe official account abstract This paper describes the analysis process of Markov transformation model in R language. Firstly, the simulation data set is modeled in detail. Next, the Markov transformation model is fitted to the real data set with discrete response variables. Different methods used to validate the modeling of […]

• ## Time series analysis model in tuoduan tecdat|r language: arima-arch / GARCH model to analyze stock price

Time：2022-5-6

Original link:Time series analysis model in R language: arima-arch / GARCH model to analyze stock price | tuoduan data technology / welcome to tecdat Original source:Tuoduan data tribe official account brief introduction Time series analysis is a main branch of statistics, which mainly focuses on analyzing data sets to study the characteristics of data and […]

• ## R language arima-garch volatility model predicts the daily return time series of apple in the stock market

Time：2022-5-4

Original link:http://tecdat.cn/?p=23934 introduction In this paper, we will try to find a suitable GARCH model for Apple’s daily return. Volatility modeling requires two main steps. Specify a mean equation (e.g. ARMA, AR, Ma, ARIMA, etc.). Establish a volatility equation (such as GARCH and arch, which were first developed by Robert Engle). To do (1), you […]

• ## Last regression algorithm

Time：2022-4-8

Background knowledge required for reading this article: linear regression algorithm and yidui programming knowledge 1、 Introduction    in the previous section, we learned that one method to solve multicollinearity is to regularize the cost function. One regularization algorithm is called ridge regression algorithm. Let’s learn another regularization algorithm-Lasso regression algorithm)1(lasso regression algorithm), the full name […]