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What is "clall" in index.Gap in "clusterSim" R package?

I am using the "clusterSim" package in my project (https://cran.r-project.org/web/packages/clusterSim/clusterSim.pdf, page 39) and I do not understand the meaning of the "clall" ...
user2702's user avatar
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1 answer
25 views

Expressing the sum of a scalar and vector multiplication in matrix form

I have the following configuration: Vector $\beta = (\beta_1, \beta_2,...,\beta_m)^T \in \mathbb{R}^m$ Lets rewrite $\beta = \sum_{j=1}^{n}\theta_j\phi_j$ where $\theta = (\theta_1,\theta_2,...,\...
dtrinh's user avatar
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1 vote
0 answers
35 views

Reference for autocorrelation formula for vectors

This post on Stack Overflow says that the autocorrelation, or self correlation, of vectors is defined as $$C(t, \{v\}_n) = \frac {1}{n-t}\sum_{i=0}^{n-1-t}\vec v_i\cdot\vec v_{i+t}$$ What is the ...
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33 views

Statistical error analysis of vector data

Reaching equilibrium in a Monte Carlo simulation often refers to a state where the system has evolved sufficiently such that its statistical properties no longer change significantly with additional ...
user366312's user avatar
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3 votes
2 answers
180 views

Autocorrelation in the vector case

I obtained two sets of data from a Monte Carlo simulation of polymer movement. One is a list of $r^2_{end-to-end}$, ...
user366312's user avatar
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0 votes
0 answers
6 views

Form of a joint distribution table of random vectors and missing vectors

I am trying to follow this lecture on variational autoencoders. When talking about random observed data $o$ with missing components $m$ (min 14:10) he states that to calculate the log-likelihood of ...
ElPotac's user avatar
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0 answers
17 views

Regression of a binary vector from another binary vector in Keras

I am trying to work on building a relationship in Keras, between X and Y where X= (1,30) and ...
stevGates's user avatar
  • 111
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0 answers
10 views

Calculating Best Linear Predictor: vector transposed translated into non-transposed vector?

I am studying the best linear predictor part of Conditional Expectation and the Projection part about the regression model. while we are looking for the Beta that minimizes S(B), I quite do not ...
Hiworld's user avatar
4 votes
1 answer
100 views

Expectation of two Quadratic form

Assume $\mathbf{h} \in C^{N \times 1}$ is a Gaussian vector with zero mean and Covariance matrix $\mathbf{R}$. Also $\mathbf{A} \in C^{N \times N}$ is a deterministic diagonal matrix. In this case, ...
Mahdi Eskandari's user avatar
2 votes
1 answer
157 views

Transformers for sales forecasting, vector output

I'm looking for a multivariable time series architecture that accepts multiple independent variables and produces multiple dependent variables. The context is sales forecasting given item, discount ...
jbuddy_13's user avatar
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1 vote
0 answers
37 views

Uniqueness of Vectors [closed]

This question is in two parts: I have a series of large vectors (where each vector comprises of values 0 and 1) that I have then concatenated into one large matrix. What I first want to know is how '...
raja's user avatar
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1 vote
1 answer
22 views

Accurracy for predicted vectors

I am currently working on a machine learning model that yields a vector of offloading decisions. An example: [-1, 0, -1, 1, 1, 0, ...] The model does not return this vector directly. Instead, the ...
YuKa's user avatar
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1 vote
0 answers
87 views

What is the derivative of a matrix with regard to a vector defined?

I had this question when I read equation (C.20) in Appendix C of "Pattern Recognition and Machine Learning" written by Christopher M. Bishop. Here I copy the equation below for reference: ...
zzzhhh's user avatar
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2 votes
1 answer
200 views

How do I calculate the variance of a Hermitian form?

Suppose $\mathbf{x}\sim\mathcal{CN}\left(\mathbf{0},\mathbf{I}_n\right)$ is a circular complex Gaussian random vector, and $\mathbf{Q}$ is a Hermitian matrix. How do I calculate the variance of the ...
Raymond's user avatar
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0 answers
458 views

Scalar similarity measure between two vectors including both angle and magnitude

I have different models, predicting a vector $\boldsymbol{v}\in\mathbb{R}^3$. Now I would like to compare the performance of these models against a baseline vector $\boldsymbol{b}\in\mathbb{R}^3$, for ...
reox's user avatar
  • 261
1 vote
1 answer
26 views

Product of elements of a vector which has very large values and very low values ordered in decreasing order (MATLAB)

I have to compute the product of the elements in a vector V. The elements of my vector are in decreasing order and go from very large numbers (eg 5e^5) to very small numbers (e.g 1.8e^-8). I am using ...
Giorgetto's user avatar
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2 votes
2 answers
758 views

How to define distance for vector of angles?

I have a vector of angles and I am looking for a method to compute the distance of my vector with any other vector of angles? I am looking for something similar to Euclidean distance but I know that ...
Aep's user avatar
  • 171
0 votes
1 answer
72 views

Removing duplicate training vectors?

As an extension to this question, for ML problems where it makes sense to remove duplicates (ie: identical data & target variables) from your distribution, in which scenarios would it (if at all) ...
eliangius's user avatar
  • 101
17 votes
2 answers
16k views

Dot product vs Element-wise multiplication

What is the different between the dot product "$\cdot$" and the element-wise multiplication notation $\odot$ in Statistics? I referred to Hamilton's Time-Series Analysis, and these seem to ...
Carl's user avatar
  • 1,216
1 vote
0 answers
116 views

rank of an expected value of a matrix

x is (a * 1) vector y is (b * 1) vector x and y are independent then what is rank(E[xy']) I know that xy' should be (a*b) matrix and since they are independent. , however I am not sure about the rank
Yuki 's user avatar
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1 vote
0 answers
309 views

Expected value of a product of two dependent random variables

Let me preface this by saying that I'm an engineer, and by no means a mathematician, so please excuse any mathematical "wrong-doing" in my explanation. I have two vectors $V_1$ and $V_2$, ...
CELFG's user avatar
  • 11
0 votes
1 answer
295 views

Length of a probability vector?

I'm doing some work on probability vectors, and came across the idea of probability vector length as a measure of how deterministic a probability vector is, as calculated using this equation: The ...
NEW2R's user avatar
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0 votes
0 answers
38 views

How do I take the derivative to $\gamma $ of $(y-x^{\gamma})^T(y-x^{\gamma})$?

I have to solve the least squares for $\gamma$ in the following problem. The model is described as $y_i = \beta x_i^{\gamma} + u_i$, where $u_i $ is i.i.d. normal with mean zero and variance $\sigma^2$...
David's user avatar
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2 votes
2 answers
1k views

Matrix and vectors, why different notation for dimensions?

If we collect data and put it into a matrix of size (100,3), we tend to say we have three-dimensional data. We think of each column as a dimension. On the other side, if we have a vector of size (100,...
Stenga's user avatar
  • 251
1 vote
0 answers
97 views

What is the entropy of multivariate data multiplied by a vector?

It is a general rule that for multivariate data $\boldsymbol{X}$ and a matrix $\boldsymbol{A}$, their entropy is $$h(\boldsymbol{A} \boldsymbol{X}) = h(\boldsymbol{X}) + \ln |\det \boldsymbol{A}|$$ (...
develarist's user avatar
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0 votes
0 answers
222 views

what is the expected value of the dot product of two vectors

I have a little question, but I don't know that well how to answer it. I have a random walker with position vector $\vec{r} = \sum_{i=1}^N \vec{r}_i$, where i is the random walker's step. Every vector ...
gengar123's user avatar
2 votes
0 answers
89 views

Estimation of a vector with a big covariance matrix

I have a Gaussian vector with a known covariance, given by a Covariogram (covariance function). Inverting this matrix (let's say of size 5000x5000 and above) is not reasonable. Is there any known ...
yoki's user avatar
  • 1,526