3
votes
1answer
32 views

p-value for weighted Pearson correlation coefficient

I'm computing a weighted correlation coefficient, using the method described here. I'd like to compute a p-value for the resulting r coefficient. How can I do this correctly, given that my r was ...
0
votes
0answers
16 views

How to obtain the complete model matrix of a mixed model?

Suppose I have a mixed model like this: ...
0
votes
0answers
6 views

Rearranging 2 discriminant function to solve for 1 parameter (to derive a decision boundary)

I have a task where I want to classify patterns from 2 classes where the samples are drawn from a bivariate Gaussian distribution. I use the 2 discriminant functions ($g_1$ and $g_2$) to classify the ...
0
votes
1answer
30 views

Measuring Statistical Significance of Binary Classification using Matthews Correlation Coefficient

Based on the following relationship between Matthew's Correlation Coefficient (MCC) and Chi Square: (MCC is the Pearson product-moment Correlation Coefficient) Is it possible to conclude that: By ...
0
votes
2answers
27 views

Hypergeometric Distribution Question

I am currently doing a self-study question that gave me the following scenario: There are 10 marbles in a jar. 7 marbles are red while 3 are blue. John wants to pick 4 marbles out to give his friend. ...
0
votes
0answers
15 views

test for variance by using chi square test in R

how can i know if these data -> 93, 91, 93, 150, 80, 104, 128, 83, 88, 95, 94, 97 58, 139, 91 provide evidence that the pop variance is greater than 0.05 (a=0.05) by chi square test in R? please ...
5
votes
1answer
105 views

Why is optimizing a mixture of Gaussian directly computationally hard?

Consider the log likelihood of a mixture of guassians: $$l(S_n; \theta) = \sum^n_{t=1}logP(x^{(t)}|\theta) = \sum^n_{t=1}log\sum^k_{i=1}p_iP(x^{(t)}|\mu^{(i)}, \sigma^2_i)$$ I was wondering why it ...
0
votes
0answers
12 views

About penalty setting in package changepoint

I have read the documentation for this package,but there is one place I don't understand, in page 7 the author set the penalty value to 1.5*log(n), where does this "log(n)" originate from? A bracket ...
0
votes
0answers
17 views

data representation with nominal, ordinal and continuous variables

Suppose I have data of this format: customer, country, location, unit price (discrete set), traffic, etc. (more nominal/ordinal variables) I want to know how country affects unit price, how do I go ...
3
votes
1answer
97 views

Exponential Distribution PDF: Why multiply by lambda?

Hoping you can help me understand the probability density function for the exponential distribution. Given that the distribution's PDF is described as follows when x > 0: $$\lambda e^{-\lambda x}$$ ...
1
vote
0answers
9 views

How do i read only lines that fulfil a condition from a csv into R? [migrated]

I am trying to read a large csv file into R. Even though the file is large, I only want to work with some of the rows that fulfil a particular condition (e.g. Variable2 >= 3). This is a much smaller ...
1
vote
0answers
20 views

Understanding stationarity with Inflation

Good afternoon, Apologies if this question is basic, I have done a lot of research, but haven't found a definitive answer online and so I'm hoping someone might be able to help me here. I am looking ...
0
votes
1answer
21 views

How do we use logistic regression (scikit-learn) to predict values

Logistic regression can help to predict a value whether it would happen or no. I'd like to know how can I do that using sklearn. I'd like to know the probability if this event would happen or no. I ...
1
vote
2answers
28 views

Trouble fitting a simple linear regression

I have been trying to do a simple linear regression of x3=Weeks Claimed against x4=Weeks compensated. I am having problems because my residual standard error is very high and also my residuals are ...
0
votes
0answers
6 views

How to create a simulation for revenue distribution in some industry?

I'm doing some research on some industry, and I'm trying to predict some revenue stats. I know that the industry worth $220M and there are 360 businesses. I assume that the business income ...
2
votes
1answer
58 views

Remove effect of a factor on continuous proportion data using regression in R

I have a data set of continuous proportions which depend on a fixed-effect factor, e.g.: ...
-1
votes
0answers
19 views

help for GEE: need for mathematical model and tests

I'm running a GEE with the following formula (run in Stata: xtgee Y K L M N O MO NO, i(household) fam(bin) link(logit) corr(ind) ...
1
vote
1answer
25 views

Hidden Markov Model: Predict observation sequence from state sequence

Given a transition matrix, starting probability, means and covariances Is it possible to predict the most likely observed sequence for a given state sequence using the above details? If yes, how? ...
1
vote
0answers
14 views

How can we predict random non-balanced events?

Prediction is the ability to statistically foretell the occurrence of future events by learning from historical data. In all the cases, if we have a large enough sample of data on how people behaved ...
0
votes
0answers
14 views

Drawing without replacement

An urn contains $X$ white balls and $Y$ black balls. What is expected number of balls you will draw before drawing a black ball? For example, if$X=2,\ Y=1$, the possible outcomes would be: ...
4
votes
2answers
82 views

Plot Pareto tails in QQ-plot for log-normal distributions

I'm working on samples that I'm trying to fit into log-normal distributions. In some cases, Kolmogorov-Smirnov test statistics is something like D = 0.0056 with an associated p-value of 0. Hence, my ...
0
votes
0answers
15 views

Why naive bayes classifier cannot perform correctly on 1 conditional probability?

I use e1071 package for naive bayes classification. My dataset is having 2 condition/feature (FF1 and FF2) to predict a class of signal (ELO or FP). When I used the following line of code: ...
1
vote
0answers
39 views

Factor analysis with binary variables using Stata 13

I am trying to do confirmatory factor analysis on data that is coded binary (0 no, 1 yes). UCLA suggests using a tetrachoric ...
0
votes
0answers
20 views

Feature selection for one class SVM

I have around 300 features, i need to choose features for one class svm. can some one tell me the ideal algorithm for this use case. I know about that for feature selection regularised random ...
0
votes
0answers
19 views

Objective function of an SVM [on hold]

I have used the svm function in the e1071 package of R software to model my data using variables selected by my feature selection method. I have obtained predictions from this model using the ...
0
votes
1answer
15 views

How to interpret results if a reference category of a categorical variable in multivariable logistic regression is not significant?

I am trying to do a multivariable logistic regression and using a normal binomial logistic regression, using binomial variable X (coded ...
0
votes
0answers
17 views

Kohonen SOM: Maximum number of neurons for any given dataset

I have an unknown data set consisting of 1024 vectors (integers with 1024 rows, 30 columns). What is the ...
1
vote
2answers
57 views

How to produce the minimum forecast error using R?

Considering that we want to use optimize() on the interval [0,1] how can I write an R code for finding the value of β that produces the minimum forecast error without using external packages like ...
3
votes
1answer
21 views

Validating assumed distributions in parametric models

When using a model that assumes a specific distribution of data, I get confused about how seriously I need to check for the assumption. For example, if we use some statistical test (e.g., based on ...
1
vote
1answer
10 views

When looking at the association between binary variables, when are odds ratios better than risk ratios and vice-versa?

The Wikipedia page lists some scenarios: While both measures are useful, they have different statistical uses. In medical research, the odds ratio is commonly used for case-control studies, as ...
0
votes
0answers
17 views

Plotting a comet like animation for multiple variables

I am trying to code a visualization with 4 variables ( Carbon emission, Energy consumption, population and year) The data set i have collected so far looks like this With C1990 representing Carbon ...
2
votes
1answer
40 views

Difference between Bayes network, neural network, Petri Nets and decision tree

What is the difference between Neural network, Bayesian network, Decision tree and Petri Nets eventhough they are all graphical models and visually depict cause-effect relationship. Thank you
0
votes
1answer
17 views

How to find correlation among dependent variables?

If I want to find how strongly a dependent variable is related to another dependent variables in a study, do I make use of multiple regression? The reason I am asking is because the book mentions ...
1
vote
3answers
104 views

In simple linear regression, what is the covariance between the error term and the residual?

In simple linear regression, what is the covariance between the error term and the residual? Model: $y_i = \beta_0 +\beta_1 x_i + \varepsilon_i$ What will be the $\rm {cov}(\varepsilon_i,\ e_i)$, ...
0
votes
1answer
26 views

Decision Tree - Splitting Factor Variables

I'm new to decision trees and I have some confusion about how factor variables and non-ordered character/string variables get handled in a split. Suppose I have a factor such as "tiny, small, medium, ...
1
vote
0answers
19 views

HMM learning from video data?

I am having a problem understanding how to learn the parameters for the HMM from observed data. Let's say that my HMM model has one hidden variable for affect(emotion) with three values/states (anger, ...
0
votes
0answers
9 views

How to get overlapping edges using igraph? [migrated]

I am trying to create a network graph with overlapping edges. ...
0
votes
1answer
40 views

lm() function in R

This is kind of a follow-up question from this post: Gradient descent vs lm() function in R? Is there any literature available for the QR decomposition concept involved in the ...
3
votes
0answers
28 views

Correlation & Regression Prediction [on hold]

I have a homework question. I have solved most of it already, but am unsure how to proceed with one specific part that involves prediction (Parts B & C). I am not looking for anyone to just give ...
0
votes
0answers
11 views

How to normalize interaction terms?

I'm training a classifier for a supervised classification problem. Some of my features interact, how should I normalize these interaction terms? For example, if x1 and x2 interact, the interaction ...
1
vote
0answers
15 views

How to graph interaction effects for panel data

I have a pretty generic question which I am guessing could be relevant to many social scientists who deal with panel data sets. What are the best practices for making graphs about interaction effects. ...
0
votes
1answer
48 views

Linear Regression Real Life Example

I am learning Machine Learning(Linear Regression) from Prof. Andrew's lecture. While listening when to use normal equation vs gradient descent, he says when our features number is very high(like 10E6) ...
2
votes
1answer
13 views

Are Restricted Boltzmann Machines better than Stacked Auto encoders and why?

So I'm learning about deep learning. I first learned about stacked auto-encoders and now I'm learning about Restricted Boltzmann Machines. However non in the papers/tutorials I read I found them ...
2
votes
1answer
18 views

Why is the decision function for probabilistic models a quotient (when we only consider two models)?

Take for example, that we want to find the probabilistic model for only two document types (doc can be + or -). I was trying to understand why the way that we classify a document model was with the ...
0
votes
1answer
22 views

decision boundary of support vector machine when data is not linearly separable

Screenshot from this video: This describes the decision boundary of support vector machine as a optimization problem with two constraints. But it seems to assume that the data points are linearly ...
-1
votes
2answers
45 views

How do we analyse likelihood in a dataset? [on hold]

I am working to analyze poverty rate using census data. I have a huge dataset. I want to extract the likelihood from this dataset in order to create patterns for energy consumption. What is the ...
3
votes
2answers
139 views

How to do multivariate machine learning? (predicting multiple dependent variables)

I am looking to predict groups of items that someone will purchase... i.e., I have multiple, colinear dependent variables. Rather than building 7 or so independent models to predict the probability ...
0
votes
0answers
19 views

Intuition behind (statistical) completeness

I was wondering if any of the members of this community would like to share his/her intuition about completeness in statistics. For the sake of "completeness", here's the definition, taken from ...
1
vote
1answer
27 views

Which machine learning method to use for geographic systems prediction?

I am trying to do experiments on geographic systems prediction. We're working on classifying the location where we sell product most. So, we need to analyze the hestorical data and predict the success ...
1
vote
1answer
33 views

Correlating two questionnaires with grouped items

I need to correlate employee engagement (gathered data using the 9 item UWES questionnaire) and organizational commitment (gathered data using the 18 item Organizational Commitment Scale). The both ...

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