All Questions

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0answers
3 views

Is it possible to get too small McFadden R^2 while at least one variable is significant?

I am quite new in logistic regression. I tried to apply a logistic regression on a dataset with 3 independent variables: Gender (Categorical- either male or female), Freq_A and Freq_B (continious ...
1
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0answers
5 views

OLS - Predeterminedness and moment condition

I'm having trouble validating if following procedure to test for predeterminedness is plausible. Given the linear model: $y_t=\beta_1+\beta_2x_{1t}+\beta_3x_{2t}+\epsilon_t$ Having $x_{2t} = y_{t+1|...
0
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0answers
3 views

Multi-task learning: weight selection for combining loss functions

I am training a system that combines two sub-systems: one for classification and another for reconstruction. Can anyone suggestion what are the common practice for weight selection for combining two ...
1
vote
1answer
3 views

How to apply INAR model to a simple time series model in Python

As a course project for Time Series Analysis, I used ARIMA for a very simple model - (Analyzing number of deaths in each episode of game of thrones and forecasting the number of deaths in the final ...
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0answers
3 views

Known Correlation between predictors

I have two predictors and an outcome, let's call them x, y and z. I know that x and y are correlated with correlation r. I am trying to construct a linear model: z = ax + by + c I have an ...
0
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0answers
7 views

What are other nonlinear transformation methods except Sigmoid, ReLU, Tanh etc?

One advantage of the MLP neural networks is the nonlinear transformation used on raw features. The popular ones used are the activation functions like Sigmoid, Tanh, ReLU, Leaky ReLU, etc. They are of ...
1
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0answers
6 views

How to calculate Bhattacharya distance for multivariate normal distributions if determinant of covariance matrix is approximated to zero

I am applying Bhattacharya distance for multivariate normal distributions $D_{B}={1 \over 8}({\boldsymbol \mu }_{1}-{\boldsymbol \mu }_{2})^{T}{\boldsymbol \Sigma }^{{-1}}({\boldsymbol \mu }_{1}-{...
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0answers
5 views

survival probability to proportional hazard ratios in r

I am using Cox proportional hazard regression to determine the association between physical behaviors (physical activity, sedentary behavior, and sleep) and mortality. to elaborate on these results, I ...
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0answers
3 views

Estimation and detection in communication problem?

I just want to get clear conceptually about the difference between detection and estimation in terms of a communication problem. Suppose I have a source and a destination. The source transmits binary ...
0
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0answers
6 views

What are properties of copula functions in simple words?

I read a lot about copula functions lately, and I think I understand the basic concept quite well. But I still have trouble understanding this summary of copula properties: Can someone help me to ...
0
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0answers
9 views

What to do if random forest still overfit after grid tuning?

I have a random forest and an ols regression. Both models i want use for an out of sample prediction. Before tuning the parameters of the random forest the default settings of the random forest yield ...
0
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0answers
11 views

Variance of a linear (and/or nonlinear) combination of an integral function (i.e., related to stochastic)

Let $I(t) = \int_{-T}^T e^{10\pi t} \{a_1X_1(t)X_2(t) + a_2X_3(t) + \dots \} dt$, where $a_i$ are constants and $X_i$ are independent random (Gaussian) variables. Is the following relation true? (or ...
1
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0answers
20 views

Proof of Rao Blackwellization

I am reading this classic paper (Information and the Accuracy Attainable in the Estimation of Statistical Parameters) by CR Rao where he introduces the idea of minimizing the variance of an unbiased ...
0
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0answers
3 views

mutation difference

I am hematology/oncology physician. i am doing project in CNS lymphoma. i have a question about the best method to calculate if there is any statistical difference in mutation frequencies between 2 ...
-1
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0answers
9 views

Explaining the regression model

Given the model: Y = a + β1 + β2 + β3 cos (∠) +β4 sin (∠) +errors resulting from a negative binormial regression, how can I explain the section of β3 cos (∠) +β4 sin (∠) given that they are the two ...
0
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0answers
10 views

Oversampling impact on semi-supervised multi-label learning

I have suggested a semi-supervised approach for the hierarchical multi-label classification task. I have included the MLSMOTE oversampling technique as a pre-processing step, and then evaluate the ...
0
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0answers
9 views

Transforming a distribution into another one?

Say I have two vectors X1 and X2, and they form two distributions. Is there any way to transform X1 so after the transformation the new_X1 will have a similar ...
0
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0answers
15 views

Why need wald test ( a squared version of t test ) when we already have t test?

It seems to me that they are basically calculate the same thing. Since we already have t test, why do we need a squared version (wald test)? Does wald test have its own advantage? For example in Cox ...
0
votes
1answer
12 views

How to calculate weighted average of hourly sales in a day

I have hourly sales data & want to aggregate it to a day level. Out of 24 hours, we are classifying 6 hrs as peak hours and 18 hrs as non-peak. Assume peak hr sales for a day as: $X_1,X_2,\ldots,...
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0answers
6 views

What units is my mean squared error if I center and scale my training data?

I have a KNN model that I used to predict the close price on houses. ...
0
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0answers
4 views

Simple slopes analysis for regression with user defined contrast codes

I am struggling with conducting a linear regression with user defined contrast codes and simple slope analyses of significant interactions between the contrast codes and categorical and continuous ...
0
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0answers
10 views

Bayesian chi-squared tests

I have a dataset with two groups of participants. Each participant performed a repeated measures task on which three types of errors could be made. I want to measure the difference in distributions of ...
0
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0answers
2 views

For Granger Causality, what inference can be made if p is < 0.05 for ssr based chi2 test, but larger for everything else for a specific lag?

I am running a Granger causality test using statstools in Python, but am struggling to interpret the results correctly. It is my understanding that if the p value < 0.05, one can assume high ...
0
votes
1answer
22 views

KL divergence between gaussian and uniform distribution

Is the KL divergence not defined because uniform has bounded support and gaussian has unbounded support? How else can I calculate the distance of my gaussian to a 'maximum entropy' distribution if I ...
1
vote
1answer
8 views

R : Conducting Oneway Anova on Continuous and Discrete Data

For a few weeks, I've been trying to figure out whether the results I've received from conducting a one-way ANOVA test are correct if so how. (I have parsed data containing null values & Alpha ...
1
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2answers
19 views

Probability of seeing a bird on a certain date based on historical notes

I have a database filled with different bird species that were seen on different dates (10 years of records). Each row in the table contains: Date, Time, Bird Species So it looks like: ...
0
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0answers
9 views

Inputting playing card values to aneural network

I am trying to create a NN to play a card game wherein each state is represented by the hands of 4 players. Every round, the hand of each player is decreased by 1 (discarded). Each player starts with ...
0
votes
1answer
25 views

Is quantile regression a special case of OLS?

Quantile regression is often advertised as a way of "predicting change in the dependent variable that is not the mean." It seems like one can do this with linear regression, however. Am I correct? ...
0
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0answers
11 views

strong and independent extra explanatory variable doesn't improve linear regression

So I already have a linear regression on 3 predictors $Y = X_1 + X_2 + X_3$. Now I have an extra predictor $X_4$. Before I put in $X_4$, the original predictor using $\hat{Y} = X_1 + X_2 + X_3$ has ...
0
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0answers
4 views

Pytorch logging: Native tensorboard support v/s TensorboardX

PyTorch recently released v 1.1.0, which has native support for Tensorboard. How does this compare with TensorboardX? I thought it would be good to list the pros and cons here. I am new to PyTorch ...
0
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0answers
8 views

Is this the right way to use 'two-parts model with recycled prediction?'

I'm researcher in health care study. 'Two-parts model' was used in severals healthcare studies. For example, when the events(e.g. readmission) occured in specific subgroup in population, only '...
0
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0answers
13 views

Minimal sufficient statistics: how should we define and interpret it?

Through my studies of statistics inference, I came into the concept of minimal sufficient statistics. However, I find it a little bit cumbersome. Could someone provide me its definition and how should ...
-1
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0answers
10 views

What numerical measures can I use for charts representing age? I.e. mean and standar deviation or 5 number summary

So I have a histogram showing ages of random people in a setting, I'm having trouble figuring out which numerical measure to use since I was under the impression that age was categorical.
0
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0answers
5 views

Given competing risks, what is the probability of an event within d steps from time t?

In competing risk analysis, we can only identify the cause-specific hazard and functions of that hazard. The cumulative incidence function (CIF) is a function of the cause-specific hazards. Because ...
2
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0answers
17 views

Standard errors on parameter estimation using OLS with autocorrelated residuals

I have always thought that the practical issue of using OLS with autocorrelated residuals was that the coefficient estimates tend to be inefficient, "the standard errors tend to be underestimated (and ...
1
vote
1answer
12 views

Quardatic term of standardized predictor in logistic regression

A random intercept logistic regression is performing to assess the association between $Y$: Disease (Yes/No) and Standardized Predictor($X_1$) adjusting for control variables ($X_2$, $X_3$) based on ...
0
votes
1answer
8 views

How would a drift diffusion model explain effects in reaction time but not accuracy?

How would a drift-diffusion model explain a case where a variable has an effect in reaction time but not in accuracy. I know that one explanation would be a speed-accuracy tradeoff, in which the ...
0
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0answers
2 views

Observation-level weighted errors for classification models

I am building a classification model, on whether a particular outcome occurs or not. For each observation, there is an associated weight which is unique by observation, and should penalize ...
1
vote
1answer
20 views

How do I avoid time leakage in my KNN model?

I am building a KNN model to predict housing prices. I'll go through my data and my model and then my problem. Data - ...
0
votes
0answers
13 views

lme4 R package: Error: number of levels of each grouping factor must be < number of observations [on hold]

I´m trying to fit a linear mixed model in lme4 using the lmer function and i have this recurrent error "Error: number of levels of each grouping factor must be < number of observations". I want to ...
1
vote
0answers
13 views

Pareto Variable Transformation

A random sample, $X_1, X_2,... X_n$ is drawn from a Pareto population with pdf $$f(x|\theta)=\frac{\theta}{x^2}I_{[\theta,\infty)}(x)$$ I've been trying to figure out the distribution of $$T=\log\Big[...
1
vote
0answers
23 views

What is this “%variance” formula doing?

I'm new to a job and they are asking me to calculate '%variance' with the following formula: $$ \frac{100\big(\frac{\bar{x} - \text{min}(x)}{\bar{x}}\big) + 100\big(\frac{\bar{x} - \text{max}(x)}{\...
1
vote
0answers
12 views

How to compare predicted accuracy and actual accuracy? [duplicate]

Consider a classifier that, given an input vector ${\bf x}$ outputs both a prediction $y'$ whose accuracy ($a \in \{0, 1\}$) can be measured, as well as a predicted accuracy that corresponds to the ...
1
vote
0answers
6 views

Recursive partitioning tree vs neural network model

I hope this question helps shed some light on trees vs neural models. I recently came across a model tree, or a recursive partitioning model. It is basically a decision tree that has linear regression ...
1
vote
0answers
15 views

What is the relationship between minimizing prediciton error versus parameter estimation error?

With the advent of statistical learning techniques, people are talking a lot about prediction error, while in classical statistics, one is focusing on parameter estimation error. What is the ...
0
votes
1answer
8 views

Is Dynamic Time Warping Affected by the Length of Time Series

I am trying to use DTW to compare pairs of EEG signals over different events. After I computed DTW distance for each event; I noticed that the longer the event is, the larger the DTW distance becomes. ...
0
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2answers
25 views

How to test whether birds spend more time in sepcific areas along a time-segmented track?

I have geolocation data on birds with 1 position per day (latitude + longitude) plus I have for each day, a corresponding binary time series that takes values 0 or 1. There is periods of minimum 10 ...
0
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0answers
19 views

I'm learning R, I need help with some questions [on hold]

If I have p=0.02 The probability that the third success is between try 20 and 25 is: The probability that the third success will come after the 20th attempt is: The probability that the third success ...
0
votes
0answers
4 views

Lasso regression with lasso2 (l1ce) vs glmnet

I'm struggling to get the same results from a lasso regression when using glmnet as when using l1ce from the lasso2 package. I've set a specific tuning parameter value for both, and tried to set all ...
1
vote
1answer
36 views

Power of a Poisson hypothesis test

A textbook of mine has online worked solutions, and the answer in the back of the book does not match the answer in the online solutions - they're not even close. My book says that the power of a ...

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