Questions tagged [references]

Questions seeking external references (books, papers, etc.) about a particular subject. Always use a more specific tag in addition.

1,771 questions
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To split or not to split a data set (when using lift to assess logistic regression)

I am designing a marketing campaign to raise money for a charity. I have a limited budget for my mailing campaign, so I have to send my mail to a selected group of people. I have data from past ...
25 views

Correlations of the variables selected by canonical correlation analysis

I do a canonical correlation analysis (CCA) to "integrate" two types of data. My advisor understands better correlations, so I made the correlations between the selected, by the CCA, variables (those ...
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kernel publications

What are some contemporary papers that provide the reader with a complex overview of kernel functions used nowadays in machine learning?
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natural language understanding algorithms [closed]

I am doing some research into how smart personal assistants work like siri, alexa etc. I have found that it is using automatic speech recognition to turn the speech into weighted text form and then ...
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Categorical Data Analysis or ML methods?

What is the difference between classical categorical data analysis (as taught by e.g. Agresti's book Categorical Data Analysis) and the classification-related methods from ML (as taught by e.g. The ...
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Help with starting a feedforward neural network for wind power forecasting

I am new to Machine Learning and Python and my task is to Predict wind power based on previous wind speed data. I have implemented this before using SVR. So I understand some basics. But now I'd like ...
259 views

Analyzing training error vs. empirical error

Suppose I have a random variable $X$ with values in $\mathbb{R}^n$, and a function $\mathscr{L}:\mathbb{R}^n \to \mathbb{R}$. In practice $X$ could represent a distribution of data, and $\mathscr{L}$ ...
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Reference request for parametric bootstrapping theory [duplicate]

Where is a good reference for the theory behind parametric bootstrapping (use MLE estimates as parameters of a distribution,then simulate from that distribution using those estimates as true values)? ...
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I am finishing 'Introduction to the Theory of Statistics' (Mood, Graybill, Boes). Now I want to learn how to do statistics but with many variables (matrices). I am considering the following books: ...
278 views

What is the basic difference between Naive and Optimal Bayes classifier? [closed]

What is the basic difference between Naive and Optimal Bayes classifier? What can an Optimal Bayes Classifier do which a Naive Bayes Classifier can't?
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N-Urns N-Color ball modelling as Markov Chain

I am trying to model a system which can, mostly, be simplified to elements of different groups changing groups among themselves. I want to understand how frequently the elements change group and how ...
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Low proportion of exposure level in some groups in multilevel model

I am working on a two-level multilevel model. My outcome is binary and I am fitting a logistic regression. The main exposure variable/explanatory variable of interest is 3 levels (0,1,2); there are ...
64 views

Do you know of business applications of Reinforcement Learning?

I'm looking for literature on the application of Reinforcement Learning (RL) algorithms in a business context. Most articles and examples in books on RL are about the application of RL to games (...
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Find the resource pages of evaluations on human learning rate against deep learning

Maybe one year ago I read a paper about the comparison between humans and machines' learning rate. It says the human can learn fast in the beginning then get slower later, machines oppositely. I lost ...
627 views

Casella and Berger vs Wasserman to acquire a good statistics foundation?

I'm interested on acquiring a strong foundation in statistics. I have just finished Introduction to Probability by Joe Blitzstein and I'm looking for a good book on statistics before moving to The ...
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Learning with noisy labels - how much more data do we need?

Suppose we have want to perform supervised learning on a dataset with binary labels. The training set is of size N, and we achieve performance (let's say, accuracy) of A% on the test set. Now, ...
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Asymptotics for Parametric MLE for Right-Censored Data

Many books and articles in survival analysis state that under the appropriate regularity conditions, that for a parametric failure time distribution and the assumption of random non-informative right-...
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What are the recent works and research scope in asymptotic inference (large sample theory)?

What are some current significant theoretical work that has been done in the field of asymptotic inference / large sample theory? What is the research scope in this field right now? Is there any open ...
143 views

What is the difference between HAC and PCSE?

I have data consist of 88 companies in 5 year (440 observations) and used 3 independent variables with 3 control variables (total 6 variables). I have already test the best model for my data and the ...
64 views

Neural network for sales revenue prediction

I'm coding up a neural network without a framework - to predict sales revenue for a shop from product prices. (Not sure if that is a common approach - as I haven't found any literature on this ...
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Frequentist Methods for Bayesians

Over time I've learned that many (most?) methods used in classical statistics can be interpreted as evaluating a Bayesian model in some plausible way while I find the standard explanations much less ...
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LASSO: selection of penalty term: “one-standard-error” rule

I'm studying LASSO regression, in particular the choice of the optimal tuning parameter. The glmnet package and the book "Elements of Statistical Learning" offer ...
114 views

Can “cross-validation” be used to choose a prior?

To be clear, I doubt I am using the term "cross-validation" correctly here; what I am suggesting also seems similar to "boot-strapping" and "hyperparameter tuning". Terminology is not my strength. ...
126 views

Is it possible that ridge logistic regression will also reduce coefficients to exactly zero? [closed]

I have 105 predictors which contain dummy, numerical, and nominal variables. The output variable is dichotomous. I ran ridge logistic regression in R, using the following syntax: ...
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Tools for self-study: Constructing and understanding systems of distributional families

I am looking for a resource that probably does not exist, but, well, hope springs eternal. I have become increasingly interested in the process by which distributions are discovered or invented. ...
138 views

Time series analysis: alternative to Brockwell & Davis [duplicate]

I have a problem - I bought a book "Introduction to Time Series and Forecasting" by Brockwell and Davis. The first chapter was ok, but now at chapter 2 I am totally lost - I cannot figure the main ...
175 views

Decomposition of single variable into mean and dispersion around mean

Consider a survey of firms of size $n$. This survey includes, among other variables, the average wage of workers in firm $i$ ($x_i$) and the number of workers in the firm ($L_i$). Both are random ...
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Unit Roots For Dummies book?

After reading the intuitive explanation of unit roots by Whuber on this website, I am motivated to find out more about them. What book would people recommend that gives a clear explanation of all ...
94 views

Elastic net consistency for time series case

I am looking for a paper that proves elastic net consistency (in estimation and model selection) for time series setting (non i.i.d. errors). I have found papers for LASSO and adaptive LASSO but after ...
1k views

Classification with 500 Categories

Currently I am working on several projects with classification algorithms. The number of categories is very high (between 100 and 4 000, but let us assume it is 500). Which algorithms are suitable ...
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Learning time series analysis in hydrogeology

Good morning, I know there are some similar questions, but I'm asking anyway since I didn't find a suitable answer for what I'm looking for. I've got some daily hydrological data about a spring, ...
173 views

Why is long-run variance a positive function of the spectral density at frequency zero?

Müller (2014) provides the following definition of the long-run variance $\omega^2$: $\omega^2=2\pi f(0)$ where $f(0)$ is the spectral density of a time series process, evaluated at frequency zero. ...
99 views

Are there good recent (i.e. year 2018) papers and discussions on the issue of “Statistics vs. Machine Learning”?

I try to get an overview about the most recent discussions of how machine learning and classical statistics differ. There is an excellent discussion on this issue here on stackexchange ( The Two ...
rule for Normality skewness $<|2.0|$ , kurtosis $<|9.0|$?
Quoting: As can be seen in Table 1, the experimental and control group distribution were sufficiently normal for the purpose of conducting a $t$-test (skewness $<|2.0|$ , kurtosis \$<|9.0|...