Multivariate analysis is used when there is more than one variable of interest in the statistical analysis.
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22 views
pdf of multivariate normal distribution
I have a question concerning some sentences in the book Structural Equations with Latent Variables (Bollen) at page 132 (bottom) and page 133 (top) regarding the pdf of the multivariate normal ...
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0answers
19 views
Multivariate linear mixed model in R
I have run into a problem with respect to an application of linear mixed effects model using lme4 package and I wondered if I could seek your help.
This is my model in a multivariate setup where ...
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1answer
49 views
Minimize a function with respect to a matrix
I have two sets of vectors, A and B. Vectors from set A live in an m-dimensional space, ...
2
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1answer
27 views
How to prove independentness of marginal/conditional (?) posterior distributions?
This is a question about exercises 4.2 and 4.3 of Jim Albert’s “Bayesian Comptutation With R” (p. 82). Note that while this might be homework, in my case it is not.
We are to prove that, given two ...
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0answers
27 views
Joint PDF change of variables
I now understand how to conduct a change of variables for a marginal PDF.
Now, given two functions that define parameter's spatially: $C_A(x)$ and $C_B(x)$, is it possible to construct the Joint PDF, ...
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1answer
33 views
Is it normal to obtain better (smaller) P values in multivariate analysis compared to bivariate one?
If a multivariate design controls for other predictors when calculating the effect of a predictor, shouldn't it give paler P values (less significant ones, or less vivid odds ratios)? I am seeing ...
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0answers
33 views
Two-way anova with interaction term: what is the point of a post-hoc test?
I have a statistics interpretation question. I've recently performed a two-way anova to identify an interaction term between my categorical independent variables (genotype + temperature) that ...
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0answers
36 views
Find the moment generating function
Find the moment generating function of $W$, when $W=X+2Y+4Z$. $~X,~Y,~Z$ are independent normal distributions $\mathcal N(1,4),~ \mathcal N(2,9) \text{ and }\mathcal N(3,16)$.
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2answers
68 views
Pre-truncation moments for truncated multivariate normal
Suppose the random variable $Y$ has a multivariate normal (MVN) distribution, and consider truncating $Y$ in some way to create $T$. Given $T$'s mean and covariance matrix, I'd like to obtain $Y$'s ...
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0answers
33 views
How do I set up a multivariate hierarchical multiple linear regression in R?
I have two continuous DVs (measurements taken on individual fish), one continuous individual level IV (fish's size), and two site-level IVs (PC1 and PC4). Sites are either take or no take. There are ...
2
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2answers
83 views
What is the difference between multivariate analysis and econometrics?
I am writing my thesis about how different factors influence stock excess returns after an M&A announcement. I haven't taken a multivariate analysis class and I have only a very basic idea of ...
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0answers
11 views
How does the Cross Validation in PRIM work?
One of the steps described in the PRIM algorithm is, after the peeling and pasting procedure, using Cross Validation to select an appropriate Box from the sequence of boxes obtained by the peeling and ...
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1answer
60 views
Compute sum of vectors drawn from multivariate normal, subject to a linear constraint
I want to compute $S = \sum_{i=1}^n x_i$ where $w^t x_i>-1, \; \forall i$ and $x_i \tilde{} \mathcal{N}(\mu, \Sigma)$ for known $w$, $\mu$ and $\Sigma$.
I know $S$ can be approximated by sampling ...
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1answer
29 views
Distance measure for multi-categorical responses
I have a data set of categorical data where each question can have more than one answer. This is a toy example:
question one: what did you eat today?
...
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0answers
34 views
How to interpret the results of stepwise multiple regression with multiple subscales in for one measure
My hypotheses for were based on the stepwise regression in which the predictors were constructs measured by four separate measures. Three of the measures have subscales. Since each subscale is put ...
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0answers
15 views
NMDS for biomass
I would like to make a NMDS with biomass of different prey groups in stomach content of fish..
I have already made one where the data matrix consists of 0 and 1, and this one went fine but are not ...
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0answers
33 views
Analysis of computer software performance
I am currently collecting data from a software system that draws conclusions about the nature of certain structures in medical CT chest scans. Structures in the chest can be classified into four ...
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0answers
11 views
How to analyze data with more than one associated categorical dependent variables?
I have some dependent variables related to the growth of a company having categories like (e.g. for variables indicating net profit, financial turnover etc.)
(1) decreasing,
(2) stable,
(3) ...
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0answers
23 views
Regression with some associated ordinal dependent variables
I have some associated categorical dependent variables that are ordinal in nature (with 4 or 5 categories). If I want to see the effect of a set of independent variables (which can be both continuous ...
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0answers
37 views
How to test for differences in 3 related measures assessed pre- & post- treatment on the same sample?
I am designing a study to compare whether one specific treatment improves Quality of life. I am using a convenience sample ($N=20$). I hope to administer three ...
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0answers
19 views
Help with choosing a DM method [closed]
I'm a student using Oracle for a data mining project, and i'm wondering if you can assist me with picking the right DM method for my data set. I'm doing an electricity consumption prediction and i ...
1
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0answers
56 views
Distribution of random variable
The chloride concentration at depth $x$ mm at time $t$ is:
$$
\text{C}(x,t)=\text{Cs}(1-\text{erf}(x/(2(D*t)^{0.5}))
$$
where $\text{Cs}$ is chloride surface concentration with Lognormal ...
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0answers
52 views
PCA and varimax references?
After doing PCA it is common that the first component describes the largest part of variability. This is important in i.e. study of body measurements where it is commonly known (Jolliffe, 2002) that ...
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1answer
83 views
Dealing with 'Don't Know' answers for a categorical outcome variable
I have a survey data with categorical outcome variable (yes, no, don't know) which reflects the acceptance of some situation by respondents. My concern is how to deal with Don't know answers, I really ...
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0answers
58 views
Proof for two-sample Hotelling $T^2$ statistic?
I've been reading "A primer of multivariate statistics" by Richard J. Harris, page 546, which shows how to derive the Hotelling $T^2$ statistic, after seeing this related but different question (I ...
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0answers
26 views
Two IVs (schools) and 3 IVs (grade levels in each) where there are 2 DVs (math and reading scores)
Is MANOVA the correct test? I am looking at 3 grade levels in each of the two middle schools. I want to compare the standardized scores (reading and math) of students in each grade level to the same ...
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1answer
45 views
Back transformation of an MLR model
I've obtained a multiple linear regression model in the form
$$
\mathrm{log}(Y) = \beta_0 + \beta_1x_1 + \dots + \beta_4x_4 + \beta_5x_1x_2 + \dots + \beta_{10}x_3x_4 + \beta_{11}x_1^2 + \dots + ...
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2answers
64 views
PCs scores from Correlation and Covariance matrices through matrix computations and prcomp
I'm want to get PCs scores through matrix approach. My calculated PCs scores for correlation matrix matches with prcomp results but the PCs scores for covariance ...
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0answers
32 views
geographic distance and mahalanobis distance
I am trying to match individuals based on monthly consumption and geographic consumption in a dense metro area. Essentially I want to create treatment and control pairs with the having both geo ...
2
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1answer
77 views
Canonical correlation analysis with rank correlation
Canonical correlation analysis (CCA) aims to maximize the usual Pearson product-moment correlation (i.e. linear correlation coefficient) of the linear combinations of the two data sets.
Now, consider ...
3
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1answer
61 views
Errors in Variables and Deming's multivariate regression: Assumptions
There has been extensive literature that puts forth a standard set of assumptions for the Ordinary Least Squares (OLS) estimator. I am very interested in working around the two classical problems of
...
2
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2answers
79 views
Is there a multivariate version of logistic regression?
Based on readings with logistic regression, it appears that you could use this analysis to make predictions about categorical variables. Does logistic regression allow you to predict multiple ...
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1answer
93 views
Backward selection in a Cox regression model
My goal is to fit a cox regression model in SAS, for which I use the PROC PHREG statement. As I am still new to regression methods, I would appreciate a little of ...
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1answer
45 views
Simulated single value based on multiple chains in RJAGS
I am using RJAGS to simulate the posterior distribution of event that a certain candidate will win the presidential election. I need to find the actual percentage that one of the candidates will have. ...
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0answers
60 views
Draw conditioned beta distributed random variables
I am trying to draw a beta distributed random variable (recovery rate), conditioned on another beta distributed random variable (default rate).
I have shape parameters $(\alpha= 0.6, \beta = 55.5)$ ...
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3answers
331 views
Automatic outlier detection in R
Our model processes millions of multivariate observations; manual outlier detection is impractical. I am looking for a method of automatic outlier detection.
I have been trying to use R package ...
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0answers
63 views
Sample size calculation for multivariate problems
I am interested in multivariate investigations. I have been trying to learn about designing such experiments where there is one dependent variable (a class/group) and many independent variables that ...
2
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1answer
225 views
Moment generating function of the inner product of two gaussian random vectors
Can anybody please suggest how I can compute the moment generating function of the inner product of two gaussian random vectors, each distributed as $\mathcal N(0,\sigma^2)$, independent of each ...
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0answers
33 views
Clustering samples from non-stationary multivariate distributions
I have dataset consisting of samples from a n-multivariate probability distribution, i.e each sample is a n-dimensional vector. The data source is known to be non-stationary in nature. I have been ...
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0answers
42 views
How to calculate vector-valued power to detect significant coefficients in a multiple logistic regression?
I'm running an experiment. Once I gather my data, I'm going to fit the model
$$
pr(y=1) = \Lambda[\alpha + \beta_1T_1 + \beta_2T_2 + \beta_3T_3 + X'\gamma +\epsilon]
$$
where $\Lambda$ indicates ...
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votes
1answer
73 views
Multivariate proportional data
I am looking for literature on what I call multivariate proportional data where a single observation is a vector of proportions that sum to 1. For example, each person weights their preferences for ...
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0answers
84 views
Hypothesis testing to determine cluster outliers
I have a cluster of $p$-dimensional data from $n$ samples which is assumed to be normally distributed as a multivariate Gaussian with sample mean ${\bar{\mu}}$ and sample covariance matrix ...
3
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1answer
153 views
A measure of overall variance from multivariate Gaussian
I am performing some regression task, where I try to discover the underlying multivariate Gaussians from a set of $n$, $p$-dimensional vectors. For example, given a split of the set into $S_i$ and ...
2
votes
2answers
153 views
how to avoid 0 determinant when sample covariance matrix has very small values
I have $n$, $p$-dimensional vectors and I am construction the $p$x$p$ covariance matrix using the following formula:
$Cov(j,k) = {1/(n-1)} {{\sum^n_{i=1}} (x_i(j) - {\mu}(j)) * (x_i(k) - {\mu(k)}) ...
2
votes
1answer
58 views
Fitting HLM models with Heavy-Tailed distribution: robust aproach to lmer?
I've been using package lmrob in R to estimate models with heavy-tailed distribution of the residuals, which I cannot correct even with transformations of the dependent variable.
I was now planing to ...
2
votes
1answer
87 views
Predict 2 responses from two co-variates
I'm not quite sure how I should fit a model that has two responses. The data consists of target (x,y) co-ordinates and actual (x,y) co-ordinates. I would like to fit a model to predict a new set of ...
3
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2answers
252 views
Ways to measure distance from multivariate Gaussian (Mahalanobis distance)
I have a cluster of p-dimensional points and given a new p-dimensional point $x$ I want to determine whether or not it is likely to belong to this cluster.
The cluster is made up of $n$ ...
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1answer
122 views
Multivariate models for ordinal variables
I would like to fit a multivariate regression model of an ordinal random vector using ordinal variables as covariates. I am wondering if there is anything implemented in R or other software that could ...
2
votes
1answer
275 views
What to do when sample covariance matrix is not invertible?
I am working on some clustering techniques, where for a given cluster of d-dimension vectors I assume a multivariate normal distribution and calculate the sample d-dimensional mean vector and the ...
2
votes
1answer
170 views
Post hoc power analysis
I have an experiment with 3 equal group sizes and 4 measures. I think the simple null hypothesis is that the three groups will be the same. Most people, however, believe that group A should do best in ...
