All Questions

1
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2answers
25 views

Convolutional neural network & recurrent neural network vs. dense feedforward networks

What are the benefits of convolutional neural networks structures and recurrent neural network structures compared to the dense feedforward network when there would be enough computing power to ...
0
votes
1answer
17 views

Odds of an event happening over a long period of time

If there is a fluctuating chance of rain throughout the day how do you calculate the chance that it will rain at some point throughout the day? For example, tomorrow there is a six hour period with ...
0
votes
0answers
5 views

about the sample size calculation of three or four groups in survival analysis

I have a question about the sample size calculation of three or four groups in survival analysis. Do you know some package in R, Stata, or other resources?
0
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0answers
7 views

Calculating test group sizes for Statistical Significance in Subject Line split Testing

Hoping for some insight or advise on the calculating ideal test group sizes in this the following scenario: Say I have a million contacts that are delivered an email campaign I want to implement a ...
1
vote
1answer
17 views

In linear regression, what would it do to center the label?

In this question linked below, it was addressed why we would center the features in linear regression. When conducting multiple regression, when should you center your predictor variables & when ...
0
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0answers
7 views

Multiple priors in Bayesian estimation

Typical Bayesian estimation equation is: Estimate = ( SampleSize * SampleEstimate + PrioriEstimateWeight * PrioriEstimate) / ( SampleSize + PrioriEstimateWeight ) Typically, the PrioriEstimate is ...
3
votes
1answer
59 views

How likely is sample A and sample B is from distribution C? [on hold]

Let's say I have a sample A: [0,0,0,1] and another sample B: [2,0,5,10,100,3,2,6] I would like to know the probability that A and B are both picked from the same population C. I tried applying a ...
0
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0answers
6 views

Endogeneity bias

For my dissertation, I am trying to determine whether chosen 'sentiment measure' have predictive power for stock returns(S&P 500). These sentiment measures consists of LN VIX for example ( change ...
0
votes
1answer
7 views

What are some good strategies for improving a classifier that works well on most of the classes but confuses 2 of them?

I'm having a classifier that tries to classify 5 different classes from a data set. It works pretty well in general, and when I'm plotting the confusion matrix almost all misses are 0, 1 or 2 max 3 ...
0
votes
1answer
35 views

What statistical technique could be used to extrapolate CO2 data

I am new to statistics but scraped data from NOAA's web site to plot CO2 level vs time. Is there a good statistical technique to extrapolate past limit of data X axis to near future like 2050? One ...
0
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0answers
9 views

Estimate for the standard error of the probability of a residual lifetime

Suppose that we estimate the survival function using the Kaplan-Meier estimator. Based on that KM-curve $\hat{S}(\cdot)$, one can then estimate the probability that the residual lifetime is larger ...
0
votes
1answer
27 views

Bootstrap Prediction Bands for Linear Regression (in R) [on hold]

I am looking for a way to implement non-parametric bootstrap to prediction bands around my regression line and confidence bands for my linear regression model. I am, however, new to bootstrap, ...
0
votes
0answers
15 views

Approximate sampling of hierarchical model conditional posterior

I am trying to apply a hierarchical model to learn the distribution of some unobservable parameters. I have assumed that these parameters follow a multivariate normal distribution (MVN) $\theta\sim\...
0
votes
1answer
13 views

What is the VC dimension of k-nearest-neighbours with k=1?

I would answer that it is $\infty$, but I have a gut feeling this may not be the correct answer... May I present my proof attempt that it is indeed $\infty$, so that you can clear any misconceptions ...
0
votes
0answers
20 views

How to update probability of logistic regression to take account new information? [duplicate]

I am at an admissions office at a college. We are trying to predict the probability that various admitted students will actually matriculate (come). We have a deadline of May 15 that the admitted ...
0
votes
0answers
8 views

Logistic regression weight doesn't converge [on hold]

When I put the weight on glm, using the logit regression model, R say that the algorithm did not converge, but when I take it off the model works normally. All I know is that I need to use weight, as ...
1
vote
1answer
44 views

Why intuitively does $\mathbb E(\frac d {d\theta}\log p_\theta(x))=0$?

Let $p_\theta(x)$ be the probability density function of $x$. Then obviously, $\frac d{d\theta}\mathbb E(1)=0$. But note that $\mathbb E(1)=\int p_\theta(x)dx$, so that $\frac d{d\theta}\mathbb E(1)=\...
0
votes
0answers
5 views

Why does kmeans after SVD result in ideal clusters

I am clustering tweets which are related to eye fashion and they are extracted using keywords like mascara, eyeliner, eyeshadow, etc from twitter. I constructed a Tf-idf matrix (tweets x words) ...
0
votes
0answers
15 views

How do I run a multiple-polynomial regression using percentile rank data? [on hold]

For each x variable, I have 500 columns of specific data where each column is the percentile rank of a given column in regards to the other 499 columns. However, since I have hundreds of x variables,...
0
votes
0answers
8 views

Kernel-weighted local polynomial smoothing in Python? (Replicating Stata/R functionality) [on hold]

I am currently using LPOLY from Stata (https://www.stata.com/manuals13/rlpoly.pdf) to create a smooth curve between different Political Pollsters: ...
0
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0answers
36 views

correlation coefficient bivariate normally distributed [duplicate]

Suppose that X,Y and X,Z are bivariate normally distributed. We have $E(X)=0, Var(X)=10$, $E(Y)=0, Var(Y)=6$ and $ρ_{xy}=0.87$ Moreover, $E(X)=0, Var(X)=10$, $E(Z)=0, Var(Z)=4$ and $ρ_{xz}=0.87$ ...
0
votes
0answers
21 views

Non-negativity of interaction information for special trivariate case

I am trying to prove that if a discrete trivariate distribution $P(X_1, X_2, Y)$ satisfies $$ P(X_1=x_1, X_2=x_2, Y=y) = \min( P(X_1=x_1,Y=y), P(X_2=x_2,Y=y) ) $$ for all $x_1, x_2, y$ then the co-...
1
vote
0answers
22 views

Binomial distribution - Variance (Experimental vs theoretical)

Just been experimenting with creating a simulation for the binomial distribution. I've made an applet in Geogebra that generates the histogram, mean of the experimental data, the variance of the ...
1
vote
0answers
17 views

What is $X$ in the fundamental equation of factor analysis?

Mulaik (2009) p135-136 writes that Let Y be an $n \times 1$ random vector of random variables whose variables are the observed random variables $Y_{1}, ... , Y_{n}$. Assume that $E(Y) = 0$ and ...
0
votes
1answer
35 views

How to analyze the relationship between two variables in a time sequence

I have a question about how to analyze the relationship between two variables in a time sequence. It is an eye-tracking experiment. I recruited two separate groups of Mandarin speakers to describe ...
0
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0answers
15 views

Frank-Wolfe vs Matching Pursuit

Which are the differences between (Orthogonal) Matching Pursuit and Frank-Wolfe algorithm? Are both applicable to the same constrained convex optimization problem?
0
votes
0answers
10 views

Does this notation in the context of reinforcement learning have an unambiguous measure-theoretic interpretation?

In the context of reinforcement learning, I have seen the formula $$V^\pi(s)=\mathbb E_{\tau \sim \pi}[R(\tau)|s_0=s]$$ and $$V^\pi(s)=\mathbb E_{a\sim \pi}[Q^\pi(s,a)]$$ Does this notation have ...
0
votes
0answers
4 views

Can the calculation of entropy be generalized to an infinite series?

For a finite problem size $n$, it's straightforward to calculate the entropy of a random variable $X_n$ for the function I'm interested in. With the particular kinds of functions that I'm studying, ...
0
votes
0answers
10 views

polynomial contrasts- bayesian analysis [on hold]

I need to check a cubic trend (polynomial contrasts) using Bayesian analysis. I tried to find solutions on line and could not find it. can i use R for that, and how ?
0
votes
1answer
18 views

2D max pool gradient propagation

I am trying to understand gradient propagation for a 2D max pooling operation when there is multiple filters for each position in the 2D grid (i.e. size = $b\times2\times2\times d$, where $b$ is ...
0
votes
0answers
3 views

What are the outputs of the inspect for SEM in lavaan?

According to the tutorial, inspect "returns a list of the model matrices that are used internally to represent the model". But what exactly are those matrices? Code: ...
0
votes
0answers
10 views

Fast Non-uniform DFT in R

So, if I want to compute discrete Fourier transform (DFT) in R, I can create my own functions like so: ...
0
votes
1answer
9 views

`dispersiontest()` estimates dispersion too small

I am using dispersiontest(fit, trafo=2) from the AER package in R to see if my data is overdispersed and what the dispersion parameter $\alpha$ is. Since I use <...
5
votes
1answer
161 views

Wilcoxon signed rank test – critical value for n>50

I have seen that someone has asked a similar question a few years ago, but unfortunately the answer is not helpful. I am in the process of estimating a Wilcoxon signed rank test with a n=63 by hand. ...
0
votes
0answers
8 views

'aqmm' - sample R code & output interpretation? [on hold]

Does anyone have sample R codes and outputs for 'aqmm' (additive quantile mixed model)? This would help me visualize how to set up my model and interpret outputs. I'm trying to build an additive ...
0
votes
1answer
39 views

How to check if means and variances are normally distributed?

From here I read that The t-test assumes that the means of the different samples are normally distributed; it does not assume that the population is normally distributed. By the central limit ...
1
vote
1answer
45 views

EM algorithm and Mean residual life

I am reading Robert Hogg's (Introduction to Mathematical Statistics) EM algorithm. In example 6.6.1 (page 370 in the 7th version), please help to explain how the following integral $$\int_a^\infty(...
0
votes
0answers
4 views

Negative transmit power in dBM [on hold]

I am calculating the transmit power of an Indoor setting for IoT devices. The receiver has 64 antennas. I am trying to minimize the transmit power. The noise power is -168dBm/Hz. The BW is 180Khz and ...
0
votes
0answers
6 views

Difference between ND5 and ND6 protein sequence datasets [on hold]

What is the difference between the NADH dehydrogenase subunit 5 (ND5) protein sequence dataset and the NADH dehydrogenase subunit 6 (ND6) protein sequence dataset? Do they contain complementary ...
0
votes
0answers
22 views

Confusion about the requirements for poisson distribution

Please refers to the below for requirements for poisson distribution. I'm confused about the 2nd bullet point with the 4th. If an event is random, that means the event cannot be associated with a ...
2
votes
2answers
21 views

How should I perform cross-validation of 10-fold?

Suppose that the circles in red are negative samples and the circles in blue are positive samples and that the green boxes are the validation set and the blank boxes are the training set. In addition, ...
1
vote
1answer
23 views

Time distibution in Markov chain

Let $E=\{A,B\}$ be a set and $X_{1,t}, X_{2,t}, X_{3,t}$ three independent Markov chains on the set $E$ with respective transition probability $P^{(1)}, P^{(2)}, P^{(3)}$ where $$P^{(i)}=\begin{...
0
votes
0answers
19 views

Inverse of covariance matrix in Linear Mixed Models

I have to find the inverse of covariance matrix in Linear Mixed Models. My model is a balanced case and it can be written as follow: $$ Y = X\beta+Z\alpha+\epsilon $$ With $$ \alpha \sim N(0, \...
0
votes
0answers
16 views

why we use Lagrangian method in SVM?

I am wondering why we are using Lagrangian method in SVM? if we have just 3 features and 1000 rows, then objective function would be $w_{1}^{2}+w_{2}^{2}+w_{3}^{2}$ but if we use Lagrangian then we ...
0
votes
1answer
8 views

Model for selecting bounding box of interest

I am using the EAST text detection model to find text boxes in an image. In all of these images I am only interested in a certain text box that has always has similar pattern (e.g. 5 digits) but ...
1
vote
0answers
39 views

Fitting Beta Distributions to Data

I am trying to reproduce some beta distribution parameters found in this published paper. I have two data sets, y1 and y2, that ...
0
votes
1answer
18 views

Computing a marginal distribution of a joint involving a delta function

Suppose that we have four continuous random variables $x,y,z,$ and $v$ and we want to compute the following integral: $$\int f(x\mid y)f(z\mid x,y)f(v\mid z,x,y)\,dx$$ There are a few conditions: $...
1
vote
1answer
22 views

Should I average data sets and calculate single parameter or average individual data set's parameters?

I am interested in calculating oxidation reaction kinetics parameters of a material at a particular temperature. Essentially I have a curve of data (mass change) vs. time for the particular ...
1
vote
1answer
22 views

Is mixed effects sensible or even superior to fixed effects when DV is standardized?

I want to investigate how a certain measure, that is standardized between 0 and 1, differs between subjects and subgroups. I am afraid that a mixed effects model would be not superior to a fixed ...
0
votes
0answers
6 views

Hard margin SVM: existence of KKT point?

I'm learning about support vector machines and ran into a question while going through the hard margin case. First I'll have to go through some steps in the problem to arrive where at I'm confused. ...

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