Questions tagged [correspondence-analysis]

Correspondence analysis is a dimensionality-reduction and mapping technique for nominal variables. It is often applied to a contingency table to explore visually affinities among row and column categories. If a table is 3+ dimensional the analysis is called Multiple Correspondence analysis.

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How can I solve “horseshoe effect” on ordination analysis (Canonical Correspondence Analysis)?

I would like to ask for help in the analysis of Canonical Correspondence Analysis (CCA) that I did in the Vegan package in R, with my dataset of species and environmental parameters. The result ...
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Calculate data for passive items in PCA

I have 50 active rows, 10 active columns and 5 passive rows and 5 passive columns. As far I have studied passive items do not contribute in SVD and their inertia/weight is also zero. I am getting very ...
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Is it possible to code in a CA the additional variables in dummies variables

I'm doing a correspondence analysis as part of a study. Unfortunately, one of the commands I use with R doesn't work because I have supplementary categorical variables that the package doesn't ...
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Display supplementary Points in CA with factorextra

On 27/03/2020 at 3:03 pm Hi, I would like to point out that I am a beginner in R Contextualization prior to my problem: My database is the result of a verbal association experiment where individuals ...
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Generalized singular value dicomposition

For a given I × J matrix A, generalizing the singular value decomposition, involves using two positive definite square matrices with size I × I and J × J respectively. These two matrices express ...
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Visualisation of Varimax Rotated Principle Component Analysis

I've carried out a PCA on a selection of brand perception data to create a brand perception map (a plot of each brand in 2D principal component space, overlaid with a projection of each 'adjectives' ...
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Interpreting the loads in a biplot

I came across a doubt about the interpretation of the biplot. I know that there are lot of questions related to this topic but I have a very concrete question, but I don't find any response. Suppose ...
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Dimension reduction - doing a PCA on the coordinates of a MCA

I have a dataset with 25 continuous variables and 2 categorical variables. I want to perform k-means clustering, so as a previous step I am performing a multiple correspondence analysis on the ...
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Principal Component Analysis on Numerical Predictors alone for Dimension Reduction

I'm trying to reduce the number of dimensions for this 'Network Anamoly Detection' dataset: https://www.kaggle.com/anushonkar/network-anamoly-detection The dataset has a total of 40 features out of ...
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239 views

How do I interpret the angles of two concentration ellipses?

Consider a map with two concentration ellipses like this below. The Vomit_y group is (almost?) perfectly vertical, while the Vomit_n group seems to be oriented at about 45 degrees. I understand that ...
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222 views

Perform k-means clustering after MCA for transforming categorical variables - provide weights to variables?

I have a very dataset with many observations (> 1 million), with mainly continuous variables and three categorical variables. After searching for clustering methods for mixed data, I decided to ...
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69 views

Using MCA/PCA together?

If I have a large dataset with continuous, discrete, and categorical data, is it appropriate to use MCA on the categorical features and PCA on the continuous, separately? I'm preprocessing my data ...
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1answer
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How to pool variables that rarely occur, particularly with respect to survey data

From the text : Multiple Correspondents Analysis by Brigette LeRoux very infrequent categories of active variables need to be pooled with others when feasible The text doesn't explain how this ...
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How many observations need to be in place for multiple correspondence analysis with a particular number of questions/categories

I'm wondering about how many observations need to be in place for a particular set of questions. If I have data as follows: ...
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Multiple correspondence analysis, definition of distance between two categories of the same question

From the text : Multiple Correspondents Analysis by Brigette LeRoux The data for this quesiton is: The definition of $f_k$ is $f_k = n_k/n$ where $n$ is the total number of individuals and $n_k$ ...
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Intuition about how the formula for “variance of axis of angle $\alpha$ with horizontal axis” works (multiple correspondents analysis)

From the text : Multiple Correspondents Analysis by Brigette LeRoux the following is given (page 32). For the purposes of this post I'm just considering there to be two dimensions that point clouds ...
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Ranking groups based on multiple criteria

My objective: To give a more sound foundation to the data I have access to. This is an exercise that is aimed to look for some structure and soundness in the interpretation of the data BUT it can be ...
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Input data for Canonical Correspondence Analysis (CCA)

I'm going to conduct Canonical Correspondence Analysis (CCA). In the tutorial I've found at: CCA environmental data are discrete ...
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Difference between two groups of people, each person “is” several characteristics

I have two groups of people, A and B (let's say 15 and 25 people). Each person in each group is characterized by a bucket of features (bucket = 6-18 features). Each feature, during qualitative phase ...
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identifying what has changed in the data year on year

I have a dataset from one year and the 'same' dataset for the next year. I would like to identify what has changed in the datasets between the years. Both datasets have the same columns. I currently ...
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How to conduct a principal component analysis on data set with large number of zeros

I have data for percentage cover of plant species in 500 sites. There are columns for 30 different species in the data set and I would like to drastically reduce this down to a manageable number of ...
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Display of dimensions in (multiple) correspondence analysis

I am getting into correspondence analysis and was wondering what the correct way is to display more than two dimensions in a biplot. I found examples with biplots showing dimensions plotted in order (...
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What assumptions about the data are require for Multiple Correspondence Analysis?

In multiple correspondence analysis, what assumptions about the data are necessary in order to find the principal coordinates for the rows and columns?
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Coding a categorical variable: 0-1 or multiple subcategories?

I'm working with R and want to run a correspondance analysis on a dataset containing, among the others, the following factors: city district: 27 levels, each corresponding to a given district ...
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Having only binary variables, why is the use of PCA still appropriate?

I often see the use of PCA on large datasets with a lot of binary variables. As i recall, the computation of the principal components is done via eigenvalue decomposition (or SVD) of the correlation ...
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149 views

One-hot encoding for SOM

I have a question regarding how I should convert categorical data to numerical data. I'm using this kdd99cup intrusion detection dataset, which has a 41 attributes and class label is the type of ...
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Is MCA equivalent to PCA when all variables are binary?

I am looking to apply principal component analysis on binary (true/false) data, and I have come across the "equivalence between PCA and MCA" (Multiple Correspondense Analysis) for binary data, but ...
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310 views

Canonical Correspondence Analysis: how to interpret results

I am using Canonical Correspondence Analysis (CCA) to analyze phytolith abundances (similar to pollen) over environmental gradients. As I am new to CCA, I read some background info. The following ...
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R vegan: RDA vs CCA, which test to answer my research question and which results to report?

(if my question should be cut up into sub-questions please let me know, since all those questions are related I decided to ask them here together as one long question) Main question As part of my ...
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I have done crosstabs and a Correspondence Analysis, having trouble reporting and interpreting Chi-Squared and Inertia?

I have data on 1500 cases with two variables (color, genus) with 5 colors and 6 genera. I almost had generally equal spread across genus, but one is disproportionately represented and has about twice ...
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3answers
393 views

What do to after hierarchical clustering and finding number of clusters

I have a dataset with 10 categorical variables with over 5000 observations, I have clustered and then found the optimal number of clusters using elbow method. Now I'm not sure what to do because I'm ...
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248 views

Is Multiple Correspondence Analysis applicable to Multi-valued Categorical Variables?

I have a data-set containing only Categorical Variables. I needed to do Principal Component Analysis on the data set. Eventually, I found Multiple Correspondence Analysis and learnt it. But, in MCA, ...
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281 views

Is there a specific name for this plot?

This plot represents the popularity of technologies in two "tools", vue and react. In left-top corner are specific technologies for vue but not for react, right-top technologies popular in both tools ...
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355 views

How I interpretate a CCA plot (made with xlstat)?

Here are the 2 CCA (Canonical Correspondence Analysis) plot I'm trying to interpretate. I did them using the appropriate function in xlstat. I want to know how I should interpretate the fact that in ...
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261 views

CCA (Canonical Correspondence Analysis) - Which version of the dataset is more adequate?

I'm currently working on a dataset of +400 samples, with 2 quantitative variables (salinity and depth) and 2 qualitative ones (sequencing method performed and nature of the sample, sediment or water) ...
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199 views

How to perform CCA with block design in R

Following example and data are completely fabricated: Suppose I am studying grooming behaviour in apes. I have four cages, 8 apes in each (4 females + males). For 24 hours I did an observations with ...
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1answer
118 views

What in cross validation from co-correspondence analysis indicates sufficient axes numbers?

The coca function at cocorresp package disponible for R provides a predictive way to relate two biological composition datasets. I need help to understand one step from examples on documentation ...
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No departure from independence term in constrained correspondence analysis

I am used to think of correspondence analysis (CA) as dissecting the weighted departure from independence through singular value decomposition, but I cannot relate this to constrained correspondence ...
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How variables (constrained loadings) are selected in a biplot CCA

I am trying to do a Canonical correspondence analysis (CCA) using the community data and chemical data. I have my family level taxonomic data as community data. In chemical data I have 18 variables: ...
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333 views

Should PERMANOVA be used to select factors for Canonical Correspondence Analysis?

I am interested in investigating the relationship between species composition and several environmental factors. My question is whether it is appropriate to use PERMANOVA to select a 'best' ...
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390 views

How to analyse multiple choice and overlapping questions in MCA?

I need to analyze a survey about entrepreneurship which has around 50 categorical variables. Therefore, after some univariate analysis, I want to apply Multiple Correspondence Analysis (MCA) in order ...
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1answer
80 views

Can Y-aware PCA be performed with binary independent variables?

I came across this tutorial for Y-aware PCA using the vtreat R package. In short, Y-aware PCA is PCA on variables that have been scaled to be in y-units. Is it valid to scale categorical independent ...
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Is there an analog to logit Y-aware PCA for correspondence analysis?

I came across this tutorial of logit Y-aware PCA for dichotomous $Y$s. Does anyone know if there is an analogous procedure for correspondence analysis? It seems that there couldn't be since the Y-...
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1answer
251 views

Multiple correspondence analysis for clustering (unsupervised learning) [closed]

I have limited stat/coding knowledge yet I try to do user clustering using unsupervised method using R. I have about 2795 observations gained from survey (mixture of categorical and scale questions). ...
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580 views

R multiple correspondence analysis loadings

I'm running a multiple correspondence analysis in R using the FactoMineR package: ...
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257 views

Displaying large number of text labels on a scatter plot

Having too many species in the data, makes the species labels overlap in a plot of a canonical correspondence analysis. This makes it difficult to interpret. Is there a reasonable possible solution? ...
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363 views

Correspondence analysis vs chi square

My data: ...
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1answer
927 views

Assumptions for Canonical Correspondence analysis

I have been trying to find the major assumptions a Canonical Correspondence Analysis makes when doing its analysis. I have had a hard time finding anything useful. I did, however, find the assumptions ...
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Do I need to standardize environmental data before canonical correspondence analysis?

I have a dataset of 15 environmental variables (soil physical and chemical properties) and about 25 "species" variables for about 40 sampling sites. I want to do a CCA to analyse the effects of the ...