All Questions

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Can a machine learning algorithm be evaluated based on a random sample?

I am trying to evaluate how well (or bad) a semi-supervised algorithm is performing on a given dataset. The algorithms assigns one of 10 labels to each data point. The dataset is huge, and it's not ...
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Correlated Random Effects Probit vs. GEE Population-Averaged Probit

My question relates to recent work on correlated random effects probit models (see these slides from Wooldridge) and comparing them to GEE population averaged probit models: Is one approach better as ...
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Repeated measures tests without “before and after” measurements

When reading about repeated measures ANOVA, until now 99% of examples are always with "before" and "after". But if I understood correctly the point of repeated measures ANOVA is not necessarily to ...
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Evaluate deviation from negative binomial model

I'm trying to figure out how to determine to what extent a sample deviates from a negative binomial model fitted to a larger population. As an example, I generated counts of doctor visits for a ...
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how to measure multichannel distances between “event” sequences

In TraMineR, seqdistmc is used to measure multichannel distances between "state" sequences. I am wondering if there is a function to measure multichannel distances between "event" sequences.
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Cox PH model selection and validation

I am trying to analyze my data using survival CoX PH in SPSS v.19 and also attempting to make different prediction models (without and with a biomarker of interest). I am a clinician (not a ...
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How to can IRT-Models be understood in GLM/ SEM Framework? (Predict Learning with added Paradata-Covariates)

I'll be working with data from an a Intelligent Tutor System similar to one studied in the KDD-Cup 2010 on Student Performance Prediction and plan to use IRT-Models to infer item and ability ...
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Cluster with distance threshold in R

I'd like to get clusters with a maximum inner distance threshold. Now I use hc <- hclust(d) and cutree(hc, numofclasses). ...
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Maximum Likelihood Estimation with Known Parameter Distribution

Consider i.i.d observation vector ${\bf x}$ from a distribution $F$ depending on vector of parameters $\boldsymbol{\theta}$ and single parameter $\alpha$. We would like to estimate parameters ...
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Adjusting significance level with for different kinds of tests (chisq, mann whitney etc.) on the same variable

I have conducted a series of tests on a single, dichotomic variable (presence/absence of a personality disorder in a neurological illness) in order to compare several things (i.e. presence of anxiety ...
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AR(1) on autocorrelated data that is not a time-series

I need to apply a regression model on observations that is not time series data but each observation presents a store and the amount of cartons that gets sent to that store. For instance ...
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Relationship between number of Principal components and Exploratory factors.

Would like to know is there any heuristic relationship between the number of components identified from PCA analysis and the number of hidden factors provided by EFA analysis on the same data set?
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How to model a skewed Student's t disribution

I have a small number of samples (5) of a large population (~10,000). The samples are percentages and hence I know from the context that no answers are possible below 0% or above 100%. From this one ...
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Hammersley–Clifford theorem

I'm reading this paper http://image.diku.dk/igel/paper/AItRBM-proof.pdf and I got stuck in page 4 with equation (1) that's based on Hammersley–Clifford theorem. I'm not good in reading set theory ...
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Difference in memory usage between gbm and blackboost [migrated]

I'm working on a database with around 250000 observation and 50 predictors (some are factors so in the end around 100 features) and I have trouble using the blackboost() function (from mboost package) ...
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Is it ok to adjust significance level according to number of comparisons in simple correlations?

a referee asked me to "split" the significance level for the number of comparison, although i am not doing repeated comparisons but just spearman correlations between variables. I have set the ...
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Model selection and parameter estimation in forecasting with a Dynamic Linear Model

I am implementing a general purpose prediction tool for time series. I want to tolerate missing values, so I decided to settle for DLMs. To make it as relevant as possible on a large number of ...
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Standard deviation of normalized data

I have a data set $y_i$ with the standard deviation $\sigma(y_i)$ for each value. The $y_i$ represent some value of photon count rate. For some reason, I normalize the data set to the average count ...
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Fitting data sample to a distribution

I'm trying to fit a data sample to a distribution. So far I have created a histogram and fitted the data with a lognormal distribution in R and made a Q-Q plot in excel (of log(benefits paid) against ...
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Dealing with different time series data in Machine Learning

I am trying to create a stock market model based on fundamental variables for the US economy. I am using R. Some of the variables I am looking to include are: GDP, Unemployment Rate, Initial Claims, ...
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if technical analysis rules for predict stock prices is unique for all cases, why should we learn neural networks? [migrated]

Is there any neural network out of the box tool that was already learned all technical rules by feeding many stock trading data?
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Monte Carlo Integration Interval Probability

Use MC integration to estimate the probability that X * exp(X) < 2.5, assuming that X ~ Gamma(1.2,3.7) ...
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On using an orthogonal series to estimate a regression function

Suppose I have a function $g\in L_2(\mathbb{R})$, and we observe variables two -vectors $(Y_i,X_i)$ such that $Y_i = g(X_i) + U_i$ for some IID error terms $U_i$. If I want to estimate $g$, I want to ...
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How to interpret results from a nonparametric Wilcoxon test [duplicate]

I did a research study that looked at pre and post test scores from a test. I was asked to run a Wilcoxon test, which I did and now I need to know how to interpret the test results but also how to ...
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Can Pearson correlation be used as a measure of fit?

In the context of multiple linear regression, is it acceptable to use Pearson correlation to discriminate how well a model fits a data set? Let's say that I have some experimental values that come ...
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Are these events independent? [duplicate]

We flip a fair coin (independently) three times. Define the following two events: A = "the number of tails is odd" B = "the first coin comes up heads" Are the events A and B independent? I believe ...
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Causality in microeconometrics versus granger causality in time-series econometrics

I understand the causality as used in microeconomics(in particular IV or regression discontinuity design) and also the Granger causality as used in time-series econometrics. How do I relate one with ...
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Comparing Percentages Between 2 Groups When Each Group's Total Percentage Exceeds 100

I am comparing the rate of specific Response Patterns A through L among students in Group 1 vs. Group 2 (rates for the first five patterns are exemplified in the table). These are response patterns ...
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How To Fix a Non-Representative Sample Using Ordinal Logistic Regression and Predict Appropriately?

After searching for this question, I did find this -- but it didn't seem to be asking the same question and I'd like to extrapolate on it if possible to get more into fixing it generally and the ...
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Measuring entropy of a 2d matrix

In this answer to the question Measuring entropy/ information/ patterns of a 2d binary matrix, the base-2 entropy of the 2-d matrices obtained from a series of moving window sum filters is measured: ...
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What Gaussian process covariance function captures an affine mean?

In the documentation for GPML, the author trained a GP with an affine mean function and isotropic squared exponential covariance function. Then there is an exercise to the reader: Try training a ...
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Best practices for extrapolating data

I have a set of variables that parameterize a logistic equation bacterial growth model. The parameters change based on temperature (e.g., growth speeds up at higher temperatures) and so it is ...
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Intelligence Squared Scoring and Winner Determination

There is an NPR podcast called Intelligence Squared. Each episode is a broadcasting of a live debate on some contentious statement such as "The 2nd amendment is no longer relevant" or "Affirmative ...
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Can I write estimate $\pm$ its standard error?

Suppose I have an MLE estimate $\hat{\theta}$ for a parameter $\theta$, and $\hat{\sigma}$ is the sqrt of the inverse of the negative of the Hessian of the log likelihood at $\hat{\theta}$. Can I ...
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What is Precision-Recall Curve?

I have a data mining assignment where I make a content-based image retrieval system. I have 20 images of 5 animals. So in total 100 images. My system returns the 10 most relevant images to an input ...
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Statistics for conditions with different number of levels

I have measured the brain activity in a group of 10 subjects who had to perform a task in real and imagined conditions, the task ...
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Statistical significance of different models [duplicate]

I ran a specification with an outcome in \$ terms, and a coefficient on a dummy variable was statistically significant. However, when I ran the exact same model with the outcome in log-dollar terms, ...
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How to do multilevel classification using R

I am trying to do a multilevel text classification using R. Is there any package in R which I can use to do it? If not, then how can I proceed using the svm or ...