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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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6 views

Bootstrap textbook [duplicate]

I used to make good reference to an excellent course on non-parametric statistics but it just got taken down. Maybe its time to find a decent text on bootstrap confidence intervals and smoothing ...
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14 views

set of tasks from discrete financial market models

I'm looking for some books with tasks from discrete financial market models. What do you recommend? Preferably solved but not necessarily.
2
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2answers
55 views

How much linguistics knowledge does one need to study Natural language processing?

I've read some NYU articles on NLP and they seem to require knowledge of syntax, semantics, sentence diagramming that I instinctively know but don't actually know. Does one actually need to have some ...
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32 views

Expert description of data visualization figures

There are good sources that teach the different kinds of plots to visualize data analysis results. Especially there are some good statistics books that show different plots to visualize data in ...
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37 views

Time Series Analysis Book/References not from Economists/Econometrics

Are there any time series books not written from an economics/econometrics perspective? I was hoping someone from biostatistics perspective wrote a time-series analysis book where terms like ...
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0answers
19 views

Two-sample KS test null distribution, reference request

I follow, more or less, the derivation of the KS test statistics's distribution that is given on Wikipedia. The following section on the two-sample test also makes sense if all I want to do is reject ...
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2answers
58 views

Is this just a consequence of Publication bias or has a name of its own? [duplicate]

Scenario: In our world, only statistically significant ($p<0.05$) results are published, everything else is rejected or not even handed in. Let's now assume an experiment is $100$ times conducted ...
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13 views

SARIMA Models with Exogenous Variables

Could someone point me to a good resource or explain how exogenous variables work in SARIMAX models?
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1answer
37 views

How biased is a statistical study in which sampling was purposely made without repeats?

It is understood in mathematical statistics that a sample (as in sampling distribution) may very well contain repeatedly the same item/subject. In practice though, it would never occur to someone ...
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14 views

Analysis of varying scenarios in least-squares regression?

First question: Is there a name for the type of analysis that is described below? (the second question is italicized in sentence below). I have a dependent variable $y$ that is related to the ...
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26 views

Modelling distance distributions

Overview I am building a model for a dependent variable which represents distance (from a more general perspective, my response can only take positive values). Moreover, it is imperative that I am ...
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1answer
27 views

In which paper did this formula appear? [closed]

I want to use this formula in my paper, but I don't know which paper or book to cite. Can anyone tell me which paper I should cite?Thank you! The formula is related to linear regression. $\hat{Y}_i =...
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1answer
21 views

Are there any clustering techniques that work well on galaxy arm dataset?

Are there any clustering techniques (k-means, GMM) that work well for this dataset?
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40 views

Who performed the first Maximum Likelihood Estimation?

I am very interested in the historical development of statistical theories. Here is the research I've done: I've tried to read two old papers of Fisher. I think the first theory paper on MLE should be ...
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2answers
39 views

What is the next probability theory book after baby Rudin, statistical inference Casella, and intro to measure theory Tao? [closed]

I have a few options, Feller-An Introduction to Probability Theory and its Applications - Vol 1, 2 Probability with Martingales Probability and Stochastics Which one should I get started? Other ...
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0answers
23 views

Shape preserving spline regression

There are shape-preserving, preserving especially positivity, monotonicity or convexity, spline interpolations such as described here and here. Are there similar shape-preserving spline regression ...
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0answers
44 views

Classification of Bayesian posterior probabilities

I have run a series of Bayesian models with flat priors in which I obtain a posterior probability distribution for my coefficient of interest. The reviewer of my paper wishes us to classify these ...
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0answers
88 views

How to interpret clusters on Markov chain time characteristics? [migrated]

I have a discrete-time Markov chain. The Markov chain is aperiodic (because self-loops exist) and is irreducible. I have found the mean recurrence time (left graph) and then sorted mean recurrence ...
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0answers
16 views

Reference Request - Bounded Discrete Multivariate Stochastic Processes

I would like to be referred to papers or textbooks about the dynamics of non-negative discrete stochastic processes under the constraint that all variables sum up to some constant. Appropriate ...
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0answers
26 views

A good literature for statistical learning theory

any recommendations for good literature on statistical learning theory? I mean, something what goes into more details than Elements of Statistical Learning, in terms of losses, empirical error ...
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1answer
17 views

What are the conditions of applicability of linear regression? [duplicate]

I am looking for a list of "Conditions of applicability of linear regression" to finish a work, but I cannot find any reference of this in any book. I founded something in several links, but in one ...
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1answer
28 views

What to do with statistically insignificant dummy/categorical variables? [duplicate]

From the research I've done the common answer is that you can not remove insignificant dummy variables from a regression. I'm having a hard time finding academic papers or books that back up this ...
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2answers
55 views

recommendation for humor book on statistics [closed]

I am looking for a humor book on statistics. The intent is not to learn statistics. I am rather thinking about funny statistical facts, funny statistical quotes, etc. Any recommendation?
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1answer
233 views

What is the support vector machine?

What IS the support vector machine? Can someone clarify my confusion? Possible answers: The SVM is the problem: given data $(x_n, y_n), n = 1, \ldots, N$ $$\min_{w, b}\frac{1}{2}||w||^2$$ $$\text{ ...
2
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2answers
73 views

Who “invented” the standard error of the mean?

I need the earliest available source. I already searched statistic books of Andy Field, Bortz & Schuster, Rasch & Friese, Wikipedia, Google and I asked 3 colleagues who teach statistics.
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36 views

Inventor of null hypothesis significance testing?

NHST is universally most used method of scientific inferencing. When was it first described in its current form and when was it first time used in the medical research? This info seems to be hard to ...
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0answers
10 views

Sources for panel data on German house prices [closed]

I'm looking for sources for panel data, preferably a database, on German house prices, it doesn't have to be free, but nothing expensive. I've tried the federal government database, but I just can't ...
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79 views

What is the “direct likelihood” point of view in statistics?

I am reading a Springer title from 1997 called Applied Generalized Linear Models by James K. Lindsey. In the preface, Lindsey writes For this text, the reader is assumed to have knowledge of basic ...
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18 views

Relationship between repeated measures ANOVA and random / mixed effect models

This is not concrete question but more a conceptual one, although a pretty low-level one I guess: When I was taught ANOVAs the 'classical' sums of squares way, I was told that repeated measures can ...
3
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2answers
95 views

Most mathematically rigorous books to learn statistics from? [duplicate]

Assume the math background is not an issue. Which books would you recommend as the most mathematically rigorous to learn mathematical statistics at the graduate level? Does Kendall's Advanced Theory ...
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2answers
29 views

What are good books for learning linear models with Python and R?

Not sure if there's a book recommendation section. I am looking for two books, one for implementation in R and one for implementation in Python. I'm hoping the books go pretty in depth on building ...
2
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3answers
127 views

Condition “Sample size > 30” for infering population proportion or mean [duplicate]

One of the conditions to use statistical inference, when estimating the proportion of a population based on the sample proportion, is that: The data's individual observations have to display ...
5
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2answers
130 views

Forcing smoothness of regression coefficients

I'm building regression models on spectral datasets: the predictors are the intensites of signal at the different frequencies. In this case the intensities at close frequency values are highly ...
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2answers
16 views

What does residual mean in the context of minimizing a function?

equation 1.2 in PRML: pattern recognition and machine learning denotes the sum of the squares of the errors between the predictions $y(x_n,w)$ and the corresponding target values $t_n$. $w^*$ ...
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0answers
16 views

Research on explaining generalizability of deep learning methods

I've read a few classic papers on different architectures of deep CNNs used to solve varied image-related problems. I'm aware there's some paradox in how deep networks generalize well despite ...
4
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1answer
350 views

Has anyone studied linear regression where the covariance matrix of the error is a function of the parameters being estimated?

Consider the multivariate linear model: $$y = X\beta + e$$ $y$ is the measured output, $X$ is the model matrix, $\beta$ is the parameter vector, and $e$ is the zero-mean error vector: $$E[e] = 0 \...
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16 views

reference request for the impact of priors in bayesian statistics

It is well known that in bayesian statistics, the prior believe can have a large impact on the estimation result. For example if you flip a coin ten times to determine whether it is loaded, a prior $...
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0answers
17 views

First historical references on auto-correlation and cross-correlation

Although the origin of Pearson's correlation coefficient is well documented (see wikipedia), I have trouble to find some of the first and historical papers introducing the motivation, the benefits and ...
3
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1answer
35 views

Book recommendations on how to conduct simulations in the context of OLS and Structural Equation Modelling

The title really says it all. Does anyone have any recommendations for well-written books, preferably with plenty of examples, on how to conduct simulation studies in the context of OLS and Structural ...
3
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2answers
65 views

Learning from multiple very varied data sets?

Suppose we have a set of objects $X$ (e.g. individual humans). Suppose also that humans can be described by a set of (potentially very high-dimensional) variables $V_i$, (e.g. $V_1$ is a picture of ...
1
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1answer
60 views

Learning problem when we have data from distributions $(p_i)$ when we care about (known) distribution $p^*$?

Suppose we have a dataset $D$ or multiple datasets $(D_i)$, with distributions $p_i:X\to \mathbb R$. Suppose there is another distribution $p^*$. All distributions are known, including $p^*$, but the $...
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13 views

Reference request: statement about jointly Gaussian RV

I found a theorem online https://people.eecs.berkeley.edu/~ananth/223Spr07/jointlygaussian.pdf Is there a secondary reference for this theorem?
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1answer
30 views

What are some books that explain the origins of or principles behind common statistical methods?

A friend of mine asked whether I knew of such a book that offers both intuitive and formal explanations of how a wide range of statistical methods were originally derived. She wasn't looking for a ...
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1answer
30 views

Unequal variance in randomized experiments to compare treatment with control?

Consider a randomized experiment to compare (one or more) treatment(s) with a control. Since groups are defined by random assignment, we should expect equal variances for a null-experiment (that is, ...
2
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0answers
18 views

Signal-to-noise-ratio, Fisher information and and “estimability”

Given a parametric statistical model, is it common to study the quantity $$ Q_{\theta} = \theta^2 I_{\theta} \, ,$$ where $I_{\theta}$ is the Fisher information? (I focus on a single parameter for ...
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1answer
50 views

Choosing among recent references on Machine Learning

For personal reasons, I need a recent reference book on ML which is not mainly focused on programming, such as for example https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/...
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0answers
28 views

(Teaching) references for computational complexity

Background: I am going to teach computational complexity (time complexity) within an introductory course in machine learning. I would like to gently introduce the notion of computational complexity ...
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0answers
10 views

Prerequisites for reinforcement learning for DTR

I want to learn how RL is used for Dynamic Treatment Regimes. What are some must-read articles or papers? Also, I am relatively new to RL and am currently reading Sutton's book on the topic. Lets ...
3
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0answers
70 views

What is topological statistics?

I came across Carnegie Mellon's Topological Statistics website, and it greatly piqued my interest. What exactly is Topological Statistics? Is it a subfield of statistics? What background (stat, math, ...
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1answer
53 views

What's a good textbook with lots of real life examples on GLM and statistical inference?

I am teaching myself statistical inference, and now I am learning about generalized linear models. I am looking for lots of serious examples to work on. I want to make sure that my understanding is ...