multivariate-testing

Forecasting for DCC Copula GARCH model in R

由 巧了我就是萌 提交于 2020-01-16 07:32:15
问题 I'm trying to forecast the Copula Garch Model. I have tried to use the dccforecast function with the cGARCHfit but it turns out to be error saying that there is no applicable method for 'dccforecast' applied to an object of class cGARCHfit. So how do actually we forecast the dcc copula garch model? I have the following reproducible code. library(zoo) library(rugarch) library(rmgarch) data("EuStockMarkets") EuStockLevel <- as.zoo(EuStockMarkets)[,c("DAX","CAC","FTSE")] EuStockRet <- diff(log

How to apply Henze-Zirkler's Multivariate Normality Test in Jupyter notebook with rpy2

由 岁酱吖の 提交于 2019-12-20 05:47:27
问题 I am interested in Applying Henze-Zirkler's Multivariate Normality Test in python 3x and I was wondering if I may do so in python in Jupyter notebook. I have fitted a VAR model with my data and the then I would like to test whether the residuals from this fitted VAR model are normally distributed. How may I do so in Jupyter notebook using python? 回答1: This is another answer since I discover this method later. If you do not want to import the library of R into Python. One may call the output

Google Site Optimizer not tracking cross-domain conversions

由 柔情痞子 提交于 2019-12-13 07:17:27
问题 I've set up three GWO multivariate tests across two domains. I've got the landing page set up correctly, and it's tracking visitors for all three tests, but conversions aren't being recorded for any of them. I've followed the instructions Google provides for cross-domain tracking, but still no dice. Here's the landing page snippet (IDs removed): <script> // Allows for multiple-domain tracking _udn = "none"; </script> <!-- Google Website Optimizer Control Script --> <script> function utmx

Linear Discriminant Analysis

由 。_饼干妹妹 提交于 2019-12-11 12:54:48
问题 In this example (from here), the remote-sensing data are used. In this data set, the observations are grouped into five crops: clover, corn, cotton, soybeans, and sugar beets. Four measures called x1 through x4 make up the descriptive variables. dat <- read.table(header=T, text=' Crop x1 x2 x3 x4 Corn 16 27 31 33 Corn 15 23 30 30 Corn 16 27 27 26 Corn 18 20 25 23 Corn 15 15 31 32 Corn 15 32 32 15 Corn 12 15 16 73 Soybeans 20 23 23 25 Soybeans 24 24 25 32 Soybeans 21 25 23 24 Soybeans 27 45 24

Multivariate Breusch Godfrey Lagrange Multiplier tests in Python

由 蓝咒 提交于 2019-12-11 07:34:47
问题 I understand that in the package statsmodel has many statistical functions that enable one to test for many issues including Breusch Godfrey Lagrange test as described here However, as far as I am concerned this only do the job for univariate case and not the multivariate case. For example, consider I have a 2 diminsional dataset say data from statsmodels.tsa.api import VAR import statsmodels.api as sm,statsmodels as sm1 data= np.random.random((108, 2)) Model=VAR(data) results = Model.fit(1)

Normalizing data in R

由 微笑、不失礼 提交于 2019-12-11 06:19:05
问题 Currently I am studying QDA and am using R software to analyze my data. The data was downloaded from the below link: https://www.kaggle.com/uciml/pima-indians-diabetes-database I want to check the QDA assumption i.e. the two groups are multivariate normally distributed, hence have used the below command in R. library(MVN) group1 <- discrim[1:500, 1:8] result<- mardiaTest(group1, qqplot = FALSE) #To check whether our data from group1 is MND group2 <- discrim[501:765, 1:8] result2 <- mardiaTest

R - multivariate normal distribution in R

由 早过忘川 提交于 2019-12-08 19:40:32
I would like to simulate a multivariate normal distribution in R. I've seen I need the values of mu and sigma. Unfortunately, I don't know how obtain them. In the following link you will find my data in a csv file "Input.csv". Thanks https://www.dropbox.com/sh/blnr3jvius8f3eh/AACOhqyzZGiDHAOPmyE__873a?dl=0 Please, could you show me an example? Raúl Your link is broken, but I understand that you want to generate random samples from empirical multivariate normal distribution. You can do it like that, assuming df is your data.frame with data: library('MASS') Sigma <- var(df) Means <- colMeans(df)

R - multivariate normal distribution in R

由 你离开我真会死。 提交于 2019-12-08 05:45:58
问题 I would like to simulate a multivariate normal distribution in R. I've seen I need the values of mu and sigma. Unfortunately, I don't know how obtain them. In the following link you will find my data in a csv file "Input.csv". Thanks https://www.dropbox.com/sh/blnr3jvius8f3eh/AACOhqyzZGiDHAOPmyE__873a?dl=0 Please, could you show me an example? Raúl 回答1: Your link is broken, but I understand that you want to generate random samples from empirical multivariate normal distribution. You can do it

R - Modelling Multivariate GARCH (rugarch and ccgarch)

由 久未见 提交于 2019-12-03 16:04:23
First time asking a question here, I'll do my best to be explicit - but let me know if I should provide more info! Second, that's a long question...hopefully simple to solve for someone ;)! So using "R", I'm modelling multivariate GARCH models based on some paper (Manera et al. 2012). I model the Constant Conditional Correlation (CCC) and Dynamic Conditional Correlation (DCC) models with external regressors in the mean equations; using "R" version 3.0.1 with package "rugarch" version 1.2-2 for the univariate GARCH with external regressors, and "ccgarch" package (version 0.2.0-2) for the CCC

Multiple inputs multivariate data visualisation

由 守給你的承諾、 提交于 2019-12-02 19:01:40
问题 I am trying to visualise multivariate data model by reading them from multiple input files. I am looking for a simple solution to visualise multiple category data read from multiple input csv files. The no. Of rows in inputs range from 1 to 10000s in individual files. The format is same of all the inputs with 4 columns csv files. Input 1 tweetcricscore 34 51 high Input 2 tweetcricscore 23 46 low tweetcricscore 24 12 low tweetcricscore 456 46 low Input 3 tweetcricscore 653 1 medium
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