Questions tagged [partial-least-squares]

A class of linear methods for modeling the relationship between two groups of variables, X and Y. Includes PLS regression.

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Prediction of independent data with PLS

In Matlab's plsregress function and in many other statistic toolboxes, there is a BETA vector returned that simplyfies the regression problem to(excluding the ...
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406 views

If there is only one variable in Y, does the first PLS component go in the exact same direction?

In partial least squares (PLS), I have multiple variables in X and only one variable in Y. If I only choose one PLS component to use for the PLS model, can I assume that this PLS component is in the ...
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443 views

Probabilistic models for partial least squares, reduced rank regression, and canonical correlation analysis?

This question results from the discussion following a previous question: What is the connection between partial least squares, reduced rank regression, and principal component regression? For ...
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Diagnostics for PLSR?

I am trying to apply sPLS2 type pf regression my matrix y has a set of clinical variables and matrix X has some gene data. I am using mixOmics package in R. My question is how to decide that my ...
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What is the connection between partial least squares, reduced rank regression, and principal component regression?

Are reduced rank regression and principal component regression just special cases of partial least squares? This tutorial (Page 6, "Comparison of Objectives") states that when we do partial least ...
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276 views

My predictors have strong collinearities, yet linear regression performs as good as partial least squares. Why?

I am trying to predict a single response from twelve explanatory variables. There exist strong correlations between my variables. The correlation matrix looks as follows, and the data have a ...
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44 views

Do I have multicollinearity? [duplicate]

I am examining the impact of 7 IVs on one DV using regression anaysis. Some of the IVs are significantly correlated with each other, which is consistent with theory. While the single OLS regression ...
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4k views

Is each of the PCA or PLS components just one of the original variables?

I am confused about what a component is in PCA and PLS. Are the components just the original variables but not necessarily in the same order? For example, in PCA, if I had 8 variables in my data, ...
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1answer
2k views

Variable selection using cross-validated PLS model when permutation test shows lack of significance

I understand that the permutation test on PLS can help to detect overfitting of the PLS model. Usually if the p-value is greater than a criterion, say 0.05, it means that the model is overfitting and ...
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13k views

How to use PCA in regression?

I'm currently reading in the Applied Predictive Modeling book about PCA for dimensionality reduction. I've read the following: If the predictive relationship between the predictors and response is ...
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242 views

Rotation in (Univariate) Partial Least Squares Regression

according to a not so recent paper (http://www.sciencedirect.com/science/article/pii/S0167947303003049), it is a good idea to Varimax-rotate the factors that have emerged by Partial Least Squares. ...
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465 views

PLS using a kernel matrix

I would like to use a kernel matrix generated with a custom kernel function to fit a PLS-DA model (I am thinking of caret's PLS-DA at the moment), with only one binary response variable in the Y block....
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695 views

Problems with implementing cross-validation for OLS, PLSR and PCR

I am new to regression methods. I am creating Multiple Linear Regression, Partial Least Squares Regression and Principal Component Regression models for my dataset, and I am a bit confused with the ...
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1answer
659 views

How to pre-process data for partial least square PLS regression in R?

I have a data frame that is consisted of 20 observations and 35 variables. I want to prepare the data for partial least square regression PLS in R. Many authors suggest: 1)Check whether the ...
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7k views

Theory behind partial least squares regression

Can anyone recommend a good exposition of the theory behind partial least squares regression (available online) for someone who understands SVD and PCA? I have looked at many sources online and have ...
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Partial Least Squares for validating a Framework

I understand that PLS can indicate the cronbach's alpha between two variables in a Framework. (i) For instance, can PLS tell us, based on the direction of the arrows, if there is causation (i.e. one ...
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1answer
346 views

How to pick the best model with cross validation?

Based on my understanding the leave one out cross validation is to hold a sample out as the test set and fit a model with remaining data and then calculate the error of prediction of the test sample ...
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329 views

Dichotomous Variables Problem

I'm currently in the process of making research about Investments. And I bumped with a problem of using variables in PLS. So would very much appreciate your advises, because I am in a dead-end for now....
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1answer
2k views

Heteroscedasticity in machine learning predictions

I am using a machine learning method (PLS) to predict a continuous variable, which currently does a pretty good job, with reasonable RMSE etc. However, the residuals exhibit heteroscedasticity, where ...
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What is partial least squares (PLS) regression and how is it different from OLS? [duplicate]

Assume we have a simple linear regression model expressed as $$y= X \beta + \epsilon,$$ where $y$ is a vector of size $n \times 1$, $X$ is a matrix of size $ n \times p$, $\beta$ is the regression ...
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538 views

PLS with more variables than data points

Does it make sense to run partial least squares (PLS) on a data set that has many more columns (variables) than it has rows (data points)? I am using plsr in R. I ...
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1answer
2k views

Using predict with PCR in R [closed]

I'm trying to follow the documentation on the pcr method in R So I do the following ...
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223 views

When do all PLS components together explain only part of the variance of the original data?

According to this question and answer, the sum of variances of all partial least squares (PLS) components is normally less than 100%: Why do all the PLS components together explain only a part of the ...
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When there is only one dependent variable, is partial least squares regression the same as principal component regression?

When there is only one response (dependent) variable, what is the advantage of partial least squares (PLS) regression over principal component regression (PCR)? My understanding is that PLS is only ...
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1answer
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What does 'iteration limit reached without convergence' mean in SAS Proc PLS

I receive the warning 'iteration limit reached without convergence' when using PROC PLS in SAS. What does this warning mean? I have 1,540 observations, 900 dependent variables and 600 independent ...
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PLS identify only peaks not troughs, and ignore certain region

I recorded a few Raman spectra for varying concentration of a substance. I processed the data in R and these are my steps: Remove baseline using baseline.corr with lambda=1e3 and p=0.01 Run PLSR on (...
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93 views

How to analyze generated components from partial least squares in SAS

I am using PROC PLS in SAS with multiple independent variables and multiple dependent variables. I would like to know how my independent variables are contributing to the scores for the first couple ...
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483 views

How to choose between different options in partial least square regression?

There seem to be several methods of performing partial least square regression. For example in pls pacakge in R, following are available: ...
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Why do all the PLS components together explain only a part of the variance of the original data?

I have a dataset consisting of 10 variables. I ran partial least squares (PLS) to predict a single response variable by these 10 variables, extracted 10 PLS components, and then computed the variance ...
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1answer
486 views

Principal component/Partial least-squares regression: can we use test data to calculate the factors?

I would like to make a PC/PLS regression and assess the resulting model's predictive power. The strategy is the classical splitting into training/validation/test sets, and using training/validation ...
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1answer
223 views

linear path models vs. pls path models (structural equation models)

Assume we have the following linear path model: Structural (inner) model: $Y_{1} = \beta_{1}Y_{2}+\theta_{1}\delta$ Measurement (outer) model: $X_{1} = \lambda_{1}*Y_{1}+\epsilon_{1}\delta$ $X_{2}...
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Neural network partial least square

I'm trying to use neural network partial least square proposed by Qin and McAvoy. The whole network trained based on the scaled values. I want to know how can I rewrite the general neural network ...
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1answer
524 views

Why is the weight vector in PLS constrained to be of unit length?

In the SIMPLS formulation of partial least squares (PLS) regression, the weights are constrained to have length of 1, $$r_a^Tr_a = 1,$$ where $a$ represents a latent component (from $1$ to $A$). This ...
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1answer
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Interaction term and partial least square regression

I am investigating the association of air pollution with birth weight. Given that there is collinearity between air pollutants, I chose to use PLS regression. To my understanding, we could use ...
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977 views

PLS PM: Multiplying outer loadings with inner path coefficients?

I'm referring to a method called PLS PM: http://cran.r-project.org/web/packages/semPLS/vignettes/semPLS-intro.pdf http://gastonsanchez.com/PLS_Path_Modeling_with_R.pdf Not going into detail, I just ...
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What is the “partial” in partial least squares methods?

In partial least squares regression (PLSR) or partial least squares structural equation modelling (PLS-SEM), what does the term "partial" refer to?
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Partial least squares for expression datasets

I'm quite new to the applications of partial least squares regression analysis, and was hoping I could get an overview of how this analysis can be applied to the datasets I have. I have two datasets: ...
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Best method of analysis for negatively skewed longitudinal environmental data?

I have a dataset composed of a dependent variable (species percent cover) and a range of abiotic variables (salinity, temperature, pH, water movement etc). It is a longitudinal study, in which species ...
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Individual factor significance in multilevel sPLS-DA

I recently was asked by reviewers to "include p-values" with my multilevel sparse partial least squares analysis. In brief, I have a nested design with two factors, say treatment and sampling region. ...
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557 views

SEM vs. Hierarchical Regression

I am comparing the outcomes of my model analysis using PLS and hierarchical regression (HR). On SPSS (for HR), I'm using (mean or summative) scores. On Smart-PLS, when I enter my variables as computed ...
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Is the PLS-DA approach for categorical variables the same as that used for PLS regression?

I understand the approach used for partial least squares for regression (PLS regression) where the PLS components are chosen such that the correlation between the scores of the PLS components of the ...
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132 views

Include confounder into partial least squares regression

I am wondering, when using partial least squares regression to investigate a research question, there is predictor component (T) and response component (U), if I want to adjust for confounders (C), do ...
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Multivariate outlier detection for PLS model

I am working with a PLS model (library pls) in R, where I am developing calibration models for NIRS data. I have been using other commercial software before that allowed me to detect outliers based on ...
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708 views

b-coefficient numerical value from pls r package

Has any body encountered a problem finding numerical values of b-coefficients while developing partial least squares regression model from spectroscopic data using ...
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1answer
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Calculate the variance explained in matrix Y by matrix X

I have two matrices corresponding to the same set of $n$ samples, with $j$ and $k$ variables, respectively ($j > 10000$, $k > 10000$). $X$ is an $n \times j$ matrix and $Y$ is an $n \times k$ ...
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1answer
5k views

Does it make sense to calculate Q2 and R2 values on PLS-DA models?

Since PLS-DA is a computational technique which deals with outcomes expressed as a categorical variable (e.g. "Yellow","Brown","Black","Green") I cannot understand how it is possible to calculate Q2 ...
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Regression in $p>n$ setting: how to choose regularization method (Lasso, PLS, PCR, ridge)?

I am trying see whether to go for ridge regression, LASSO, principal component regression (PCR), or Partial Least Squares (PLS) in a situation where there are large number of variables / features ($p$)...
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PLS regression analysis based on Likert scale

Can dependent variable for PLS be based on Likert scale? As i understand, dependent variable needs to be continuous. I wish to multiply frequency (i.e. integer value 3) with rating coming from ...
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Partial least squares regression for categorical factor in R

I adjust the partial least squares regression for one categorical factor (2 levels – be or nottobe) with with the ...
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830 views

Partial Least Squares structural equation modeling

Im calculating a Structural Equation model with Partial Least Squares (with R). Lets say a simple example: two Response values (R1, R2) are combined to a latent variable RespLV = weight1*R1 + ...