Questions tagged [references]

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

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0answers
20 views

Expected value for f(x) [on hold]

I am reading an article and trying to extend their case to a multivariate case. I have the function $f_{i} (x)=\frac{1}{|Σ|}f_{0}((x-μ_{i})'Σ^{-1}(x-μ_{i}))$, and I am trying to find $∫xf_i^2 (x)dx$ ...
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1answer
794 views

Who invented profile maximum likelihood estimation?

Could anyone give me some information on who invented profile maximum likelihood estimation or who first use profile maximum likelihood estimation and the short history of profile maximum likelihood ...
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9answers
1k views

Reference with distributions with various properties

I often find myself asking questions like, "I know this variable $x$ lies in $(0,1)$ and most of the mass lies in $(0,.20)$ and then declines continuously towards 1. What distribution can I use to ...
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2answers
135 views

Book recommendation for ANOVA and linear models

I'm looking for a good self study book to study Linear Models and ANOVA. Books which are more mathematical works better. Please recommend.
2
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3answers
109 views

Regression model with aggregated targets

Similar as in this self-answered question, I want to ask about possible approaches for modelling data with aggregated targets, i.e. things like $$ \bar y_{j[i]} = \alpha + \beta x_i + \varepsilon_i $$...
13
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2answers
215 views

Literature review on non-linear regression

Does anyone know of a good review article for the statistical literature on non-linear regression? I am primarily interested in consistency results and asymptotics. Of particular interest is the ...
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0answers
16 views

“Simple” boundary correction method in kernel density estimation

I'm new to kernel density estimation and have a rough idea on boundary bias. When correcting for boundaries, I tried to use boundary correction method as "simple" which is available in R. Once I ...
1
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1answer
31 views

Literature on Bayesian stuff with Normal Distribution?

I am writing something on Bayesian Analysis involving the normal distribution. I know that the conjugate prior is the so-called normalized Gamma inverse distribution, I know the update rule for the ...
5
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3answers
54 views

Resources similar to Mosteller's 'Fifty Challenging Problems in Probability'

Frederick Mosteller's book 'Fifty Challenging Problems in Probability' is a collection of interesting and unusual problems. Can we collect similar resources (online or published) here? The key ...
21
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3answers
7k views

Neyman-Pearson lemma

I have read the Neyman–Pearson lemma from the book Introduction to the Theory of Statistics by Mood, Graybill and Boes. But I have not understood the lemma. Can anyone please explain the lemma to ...
1
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0answers
22 views

Summary statistics for bipartite networks

I have a large bipartite network that I would like to summarise. So far, I have found the following summary statistics: Degree centrality Graph density Modularity Nestedness I have not found a ...
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0answers
22 views

Properties not yet proven for neural networks but proven for regression

This question is a bit vague: Are there any properties postulated for feed-forward neural networks which are not yet proven and have a known analogue in classical linear regression analysis?
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0answers
7 views

Reference request: Table of probability mass function / probability generating function pairs?

I have a probability generating function $G(z) = \sum_{k=0}^\infty z^n p(n)$ for a discrete random variable which is somewhat complicated. I would like to "invert" it to obtain the pmf $p(n)$, which ...
1
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0answers
12 views

Extension of Potts model with non-constant interactions?

Is there any work that extends (allows) Potts model to have non-constant interactions between the lattice points? Specifically, the interaction matrix is a symmetric matrix that can have both positive ...
3
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1answer
326 views

Theoretical Justification for Cross Validation

I get it, cross validation works. I'm wondering if there is an literature out there giving any theoretical justification for cross validation. My thought is that there should be, at least, something ...
0
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1answer
51 views

Batch Normalization or just z-normalization as a Nonlinearity

It is already common to do something "like"**(see asterisks below) z-standardization of the outputs of one neural network layer before passing it to the next. z-standardization would transform the ...
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1answer
26 views

Articles that work with covariates for mean, variance, and correlation simultaneously

Does anyone know of articles in which, in addition to modeling the mean parameter, are also modeled the variance and correlation parameters? I know the double generalized linear model, but they only ...
0
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1answer
44 views

Does increasing sample size by reducing universe invalidate previous data?

My team and I are working on a project that aims to measure the impact of adding more public bicycle stations in Mexico City on private vehicle traffic. We selected 100 key locations, which are spread ...
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0answers
31 views

Are there any recent advances on the combination of deep learning and graphical models?

Could you please introduce some recent papers on this? How to deal with the (approximate) gradient descent for graphical model inference, and then integrate it into the stochastic gradient descent? I ...
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2answers
6k views

Gradient boosting decision tree implementation

I am willing to implement my own GBM. I have been looking - unsuccessfully - for a clear article describing the implementation of gradient boosting machine for decision trees. Sources like this are ...
0
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1answer
159 views

Master List of ML algorithms by type

I was asked today if there was a master list of machine learning algorithms broken down by type. I searched for one, but didn't find a good list. I was going to write one for my friend, but decided I ...
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0answers
60 views

book recommendation - statistics in medicine

Could you recommend a book about the implementation of basic statistic concepts in medicine? In particular, I want to find a book that covers principal component analysis, correspondence analysis and ...
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0answers
11 views

How to start with ARIMA? [duplicate]

Which book or standard procedure to read first? My basic want is to start on Time-Series Analysis. I need to understand ARIMA from beginner level and be able to answer basic questions on it.
18
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3answers
369 views

Why is there -1 in beta distribution density function?

Beta distribution appears under two parametrizations (or here) $$ f(x) \propto x^{\alpha} (1-x)^{\beta} \tag{1} $$ or the one that seems to be used more commonly $$ f(x) \propto x^{\alpha-1} (1-x)^{...
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2answers
83 views

Alternatives to The Statistical Sleuth?

I am looking for a simple and concise book on statistics (t-test, ANOVA and all its variants, linear regression, etc.), centered on data analysis. I am not interested in theory or proofs, but just ...
1
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1answer
476 views

Gamma distribution and applications

I'm looking for references to read about gamma distribution and applications in industry or in quality control. I had a look at statistical methods for reliability data (Meeker and Escobar). It has ...
11
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2answers
293 views

Is it worthwhile to publish at the refereed wiki StatProb.com? [closed]

Background I read about StatProb.com from a comment on Andrew Gelman's Blog. According to the website, StatProb is: StatProb: The Encyclopedia Sponsored by Statistics and Probability ...
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0answers
42 views

Who to attribute information gain to?

I am writing a paper where I examine information gain specifically with regards to feature selection and am wondering what the proper reference should be. I have looked all over and I can't find a ...
2
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1answer
44 views

What is the best syllabus for an under-grad class in Statistics for engineer students?

I teach statistics to under-grad engineer students who major in Information Technology (IT). My students first learn a (prerequisite) course on probability where they learn combinatorics, different ...
2
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1answer
86 views

Good Text for Shapiro-Wilk Test

I was wondering if anyone can give me some good texts for understanding the Shapiro-Wilk test. I'm searching for an intermediate level text, not too simple like the wikipedia page (it gives very ...
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0answers
35 views

error in the book “A first course in Machine Learning”?

I am reading the book "A first course in Machine learning". At page 74 when talking about the maximum likelihood solution, considering the data matrix X 2x2, he ...
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0answers
43 views

Bounds for Distribution of X/Y with fixed marginals of X and Y

Bound for distribution of sum of RVs with fixed marginals has been discussed, for example in Best-possible bounds for the distribution of a sum — a problem of Kolmogorov. Is there similar paper ...
6
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1answer
142 views

is there a book on stats similar to Kallenberg's on probability?

One may find this question a duplicate, but my search through CrossValidated did not give satisfactory result. So I am posting this question and explaining what I want. I need a book such that if one ...
0
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1answer
59 views

Decide for three Bernoulli samples are some of them from the same distribution (or non of them) ? (do not use t-stat ) [duplicate]

Please pay attention, I am interested in Bernoulli samples, and hope to find criteria specific to Bernoulli distribution, not using s Student's t-statistics or Mann-Whitney or etc., since their use ...
1
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1answer
115 views

Poisson Binomial Distribution - confidence intervals

I'm working on a project which involves multiple trials for which the probability of success is not the same across trials. Given the unequal probabilities per trial, I'm using the Poisson Binomial ...
1
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0answers
307 views

Looking for derivation of Shannon entropy of binomial distribution

According to Wikipedia, the Shannon entropy of a binomial distribution is $\frac{1}{2}log_2 (2\pi*e* np(1-p)) + O(1/n)$ Does anyone know where I can find a derivation?
15
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2answers
3k views

Run-time analysis of common machine learning algorithms

Does anyone have reference to a summary of run-time analyses for common machine learning algorithms (different flavors of NN, SVMs, etc)?
0
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1answer
241 views

P Value interpretation in K fold Validation

I am validating a credit risk model. I did a k fold validation to check the stability of the estimates. The estimates of the model are quite stable but the variables now have a high P value(above 0.1) ...
4
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1answer
63 views

geometric methods in the design of experiments

In the preface to Coxeter's well-known Introduction to Geometry, he writes "Geometry is useful not only in algebra, analysis, and cosmology, but also in kinematics and crystallography (where it ...
1
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1answer
62 views

Maximum Likelihood with penalization

Can someone please give me a reference where I can find more info on the method of Poisson maximum likelihood maximization with smoothing hyperparameters Here we want to find the parameters Ws and &...
0
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0answers
10 views

What is the relationship between risk ratio and weight of evidence?

I've been reading about risk ratios as typical measures in clinical settings. In finance and credit literature, there is the weight of evidence measure to encode and study variables. Is there a ...
2
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1answer
88 views

What does one expect from a great course of time series? [closed]

I usually teach finance (asset pricing and equilibrium models), quantitative economics (linear algebra and optimization), econometrics, computer science introduction to programming and machine ...
2
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2answers
64 views

Classification tasks where machines achieve significantly higher accuracy than humans

Spam filtering is an example of classification task where machines achieve approximately similar accuracy as humans. On the other hand, Asirra (recognizing cats and dogs in images) is an example where ...
0
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1answer
66 views

Now that I've theoretical foundation in ML, where can I find simple, already solved, practice exercises to better my understanding of data science?

I've studied and understood well quite a bit of theoretical concepts of Machine Learning (except Deep Learning): e.g. the mathematics behind several classification and clustering algorithms, SGD and ...
1
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1answer
202 views

Dynamic panel data

Can anyone please recommend a good source (academic and basic) for understanding the concepts of dynamic panel data estimation methods and why its preferred over static data analysis?
3
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0answers
76 views

What are good sites or blogs for statistical analysis case studies?

I'm NOT looking for articles that focus on presenting R/Python libraries or how-tos on new/cool/advanced techniques or "data science". I AM looking for articles that show how classical, established ...
0
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0answers
21 views

Advice on preliminary ML resources [duplicate]

So I’m a first year student and I really want to get better at machine learning. I’ve implemented GANs, Deep Q Learning, autoencoders etc using Tensorflow. I haven’t really played around with linear ...
55
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10answers
3k views

What are some examples of anachronistic practices in statistics?

I am referring to practices that still maintain their presence, even though the problems (usually computational) they were designed to cope with have been mostly solved. For example, Yates' ...
165
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76answers
207k views

Statistics Jokes

Well, we've got favourite statistics quotes. What about statistics jokes?
3
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0answers
364 views

Data prep / variable creation for predictive models

I was reading a couple of the write ups from a Kaggle challenge: Here is one and another and it got me wondering about variable creation in data mining and why there seems to exist so few texts or ...