The multivariable tag has no wiki summary.
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0answers
13 views
Attribution Analysis for Multi-Variable Equation
I have a multi-variable equation in which I am trying to run an attribution analysis for the change from one period to another. For example:
Initial Period
X*Y+Z = 100
Where X=2
Y=40
Z=20
Second ...
0
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2answers
118 views
How to get from joint distribution F(x,y) to f(x,y) to calculate the marginal distribution of X?
I have this homework question I'm not 100% sure how to tackle.
I have a random vector with joint distribution function F(x,y) and am asked to find the marginal distribution function.
I think need ...
2
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3answers
307 views
Does adding more variables into a multivariable regression change coefficients of existing variables?
Say I have a multivariable (several independent variables) regression that consists of 3 variables. Each of those variables has a given coefficient. If I decide to introduce a 4th variable and rerun ...
-1
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1answer
203 views
Logarithmic regression of form $y=a+b \log(x_1)+c\log(x_2)$ using R [closed]
How can I fit a logarithmic regression equation of form $y=a+b (\log (x_1)) + c(\log(x_2))$ on a data set using R?
Here the main concern is that data contain zeros multiple times, so R will give ...
1
vote
2answers
105 views
I need a model that can predict based on multiple variables. How do I get started?
I have a problem where I have to predict a variable X that is dependent on several other variables a,b,c,d... I have the data containing the values of these variables a,b,c,d.. and also X up to a ...
2
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1answer
202 views
What to do when there are too many variables?
I found that the probability of an event occurring is an algebraic function of all the probabilities that I want to find;
$$P(v_1,v_2,v_3,...,v_n)=p_{collected}$$
For small $n$, it would be easy to ...
1
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0answers
102 views
References about univariable vs multivariable variable selection
Suppose I have variables $X_j$, $j=1,\ldots,p$, some of which are correlated, and some continuous output $y$.
I want to rank the variables by importance. One way is to do an association test of each ...
2
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2answers
663 views
Multiple dependent variables in factorial design
I have a 2x2x2 factorial design with two dependent variables (lets say height and weight). I can examine the effect of the three factors for each dependent variable separately. But I also want to ...
4
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1answer
2k views
Readdressing the semantics of multivariate and multivariable analysis
There was a post once upon time dealing with the differences of multivariable and multivariate regression. I have seen the relevant post here. However I am having this debate with a colleague and ...
2
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2answers
126 views
Visualizing a 5x5x5 data set
I'm trying to visualize a matrix of 3 datasets.* For the sake of example, let's say I have a list of hats, coats and shoes, and I want to display a 2D grid/visualization of each possible combination.
...
6
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4answers
751 views
What are the software limitations in all possible subsets selection in regression?
If I have a dependent variable and $N$ predictor variables and wanted my stats software to examine all the possible models, there would be $2^N$ possible resulting equations.
I am curious to find ...
3
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1answer
219 views
Estimating probability distribution function of a data stream
I have a very large number of observations. Observations arrive sequentially. Each observation is an $n$-dimensional vector (with $n \ge 100$), is independent from the others and is drawn from the ...
5
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1answer
151 views
From Marginal Exp-Norm Distributions to What Conditionals and Joint?
I have (trivariate: multivariate with three variables) data that appears to be good empirical and reasonable theoretical fit for a (univariate) convolution of an exponential and a normal distribution ...
6
votes
1answer
665 views
Finding marginal densities of $f (x,y) = c \sqrt{1 - x^2 - y^2}, x^2 + y^2 \leq 1$
As the title says, I'm looking for the marginal densities of $f (x,y) = c \sqrt{1 - x^2 - y^2}, x^2 + y^2 \leq 1$.
So far I have found $c$ to be $\frac{3}{2 \pi}$. I figured that out through ...
7
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2answers
757 views
Computing best subset of predictors for linear regression
For the selection of predictors in multivariate linear regression with $p$ suitable predictors, what methods are available to find an 'optimal' subset of the predictors without explicitly testing all ...
18
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7answers
734 views
Is there an accepted definition for the median of a sample on the plane, or higher ordered spaces?
If so, what?
If not, why not?
For a sample on the line, the median minimizes the total absolute deviation. It would seem natural to extend the definition to R2, etc., but I've never seen it. But ...
3
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2answers
462 views
Orthogonal parametrization
In general inference, why orthogonal parameters are useful, and why is it worth trying to find a new parametrization that makes the parameters orthogonal ?
I have seen some textbook examples, not so ...
2
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1answer
444 views
Dataset for multi class perceptron
I am developing a multi-class perceptron algorithm and was wondering if there are any datasets that could be used to test a multi-class perceptron? - A dataset where the classes are linearly separable ...
38
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14answers
4k views
What is the best way to identify outliers in multivariate data?
Suppose I have a large set of multivariate data with at least three variables. How can I find the outliers? Pairwise scatterplots won't work as it is possible for an outlier to exist in 3 dimensions ...
2
votes
1answer
178 views
Multivariate Interpolation Approaches
Is there a good, modern treatment covering the various methods of multivariate interpolation, including which methodologies are typically best for particular types of problems? I'm interested in a ...
