"References" is our generic tag for questions seeking information about books, papers, presentations, videos of lectures, on-line tutorials, etc., regarding any subject matter that is on-topic for Cross Validated.

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6
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41 views

Textbooks on Matrix Calculus?

See this question on Math SE. Short story: I read The Elements of Statistical Learning and got frustrated when I was trying to verify some of the results, e.g., given $$\text{RSS}(\beta) = ...
0
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0answers
10 views

Class weights in unbalanced SVM classification

The answer to this question says that class weights for unbalanced SVM classification can be picked so that that sums of the weights for each class are equal. Should this be done before ...
0
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0answers
8 views

Good resources on General Linear Models

Unlike some other topics in statistics for which I usually find an abundance of good detailed resources, I seem to have a hard time finding good ones about GLM. I was taught about it in statistical ...
-1
votes
2answers
55 views

Kernel of a Normal Distribution

From Wikipedia , The kernel of a probability density function (pdf) or probability mass function (pmf) is the form of the pdf or pmf in which any factors that are not functions of any of the ...
-1
votes
0answers
35 views

What is a data analysis book that is as math intense as Lattin's Analyzing Multivariate Data and Everitt's Applied Multivariate Data Analysis? [on hold]

What is a data analysis book that is as math intense as Lattin's Analyzing Multivariate Data and Everitt's Applied Multivariate Data Analysis? Data analysis textbooks usually don't have as many math ...
0
votes
1answer
29 views

Autocorrelation or Serial Correlation

Autocorrelation is also known as serial correlation . Why is the terminology serial used ? Is there anything unserial or ...
0
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2answers
40 views

Correlation Coefficient for lag $k$ in Time Series Data

Formula of Pearson Correlation Coefficient is : $$r_{xy}=\frac{\sum_{i=1}^{n}(x_i-\bar x)(y_i-\bar y)}{\sqrt{\sum_{i=1}^{n}(x_i-\bar x)^2}\sqrt{\sum_{i=1}^{n}(y_i-\bar y)^2}}$$ In Time series ...
1
vote
2answers
106 views

Multivariate Data

There is a built-in data set USArrests data in R software . ?USArrests We use this ...
0
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0answers
12 views

Classifying Signal Curves [on hold]

I am interested in knowing some literature references regarding the following scenario: Given a set of signals, i.e., functions: $\mathbb{R} \rightarrow \mathbb{R}$, what are common approaches for ...
0
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0answers
7 views

Sources for State level consumer spend in USA [closed]

To help with something I am working on, I need sources which can given me the consumer spend in USA (doesnt matter if it is cash or non-cash) at a monthly/quarterly level. You people have any sources ...
2
votes
0answers
46 views

Reference for this claim: important features in data can be “hidden” in the higher PCA axes that are typically thrown out [duplicate]

I remember reading a paper a while ago that demonstrated some cases in which PCA would fail to capture important features of a data set in the first few principal components, but where those features ...
2
votes
2answers
74 views

Machine Learning for Image Processing book recommendation

I'm searching a good (and compact) book about multivariate pattern analysis in images with machine learning techniques. I took a machine learning course and used for it the Bishop book but I found it ...
0
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0answers
15 views

Where I can find resources to learn how to calculate the sample size representativeness, and realiability and validity of questionnaires?

I'm totally newbie in psychometrics but starting from a research paper with full data I would like to understand: how to calculate if the sample size is representative; how to calculate reliability ...
2
votes
1answer
21 views

Random Effect Model and Response Surface Methodology

In Design and analysis of experiment , Random effect is defined as : An experimenter is frequently interested in a factor that has a large number of possible levels. If the experimenters randomly ...
2
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0answers
18 views

Johansen's cointegration test in small sample under non-normality

I am looking for references regarding the behaviour of Johansen's cointegration test (trace test, perhaps also eigenvalue test) in small samples with non-normal innovations. I wonder how robust the ...
0
votes
0answers
11 views

adjustment of lift measure

Lift is a measure widely used in many domains. However, it is known to have a problem for infrequent counts. What are the solutions for this type of problem? In frequent pattern mining hyper-lift was ...
1
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0answers
17 views

Pseudo-random numbers generators references

What can I read about pseudorandom numbers generators? In fact, I do not know even the difference between random and pseudorandom numbers. Could you please offer some introductory level notes, ...
1
vote
1answer
26 views

Multilevel Model

Multilevel Model , Level 1 regression equation: $$Y_{ij}=\beta_{0j}+\beta_{1j}X_{ij}+e_{ij}$$ Level 2 regression equation: $$\beta_{0j}=\gamma_{00}+\gamma_{01}W_j+u_{0j}$$ ...
1
vote
0answers
26 views

Intercept-Only Model

In this example, the model is $$Y_{ij}=\beta_{oj}+\beta_{1j}X_{1ij}+\beta_{2j}X_{2ij}+e_{ij}\ldots(1)$$ A class with a high intercept is predicted to have more popular pupils than a class with a ...
0
votes
0answers
9 views

Assumption of constant variance in every classes of multilevel regression analysis

In this post, in the referred book , it is also written that : The residual errors $e_{ij}$ are assumed to have a mean of zero, and a variance to be estimated. Most multilevel software assumes ...
0
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0answers
28 views

Multilevel Regression Analysis Example

Here is an example . I have not understood some points which I have highlighted and adjacently asked what I have not understood. Assume that we have data from $J$ classes, with a different number ...
4
votes
1answer
101 views

Neyman-Pearson lemma

I have read the Neyman-Pearson lemma from the book Introduction to the Theory of Statistics . But I have not understood the lemma . Can anyone please explain me the lemma in plain words ? What ...
0
votes
0answers
8 views

References for learning text stemming

I am trying to learn and experiment with text stemming. My ultimate goal is knowledge extraction from scientific text and corpus with emphasis on contextually multiplicity. But text stemming and ...
3
votes
2answers
90 views

Variance stabilising transformations

Can someone please point me to a textbook or lecture notes that explains what variance stabilising transformations are? I can only find bits and pieces on google. I don't know a lot of statistics, ...
1
vote
2answers
66 views

Best books for General and Advanced Statistical Data Analysis and Modeling [closed]

I would like to know which are your favourite books on General and Advanced Statistical Data Analysis and Modeling. In particular, I would like to know which books you consider the must-have for an ...
0
votes
2answers
55 views

Lifetime or Failure Time

Lifetime / Survival time / Failure time : the time to the occurrence of event (always nonnegative) . Lifetime and Survival time can be synonymous . ...
4
votes
2answers
118 views

On forecasting, the mean squared error and realized volatility

Say one has finished estimating a correctly specified GARCH(1,1) on a daily time series and now wants to evaluate the accuracy of the one step ahead forecasts what steps or tests could one do? I ...
2
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0answers
28 views

Sample lower bound for binary classification in Linear Discriminant Analysis?

Below is a description of this problem: Suppose the label $Y\in\{1,0\}$ in binary classification satisfies $\Pr[Y=1]=\Pr[Y=0]=\frac{1}{2}$, and $p(X|Y=1)=\mathcal{N}(\mu_1,\Sigma)$, ...
1
vote
2answers
174 views

Consequence of Multicollinearity

In case of perfect multicollinearity the predictor matrix is singular and therefore cannot be inverted . Under these circumstances, the ordinary least-squares estimator $\hat\beta=(\Bbb X'\Bbb ...
0
votes
1answer
38 views

problems in doing logistic regression with unbalanced sample, give me some references

I have a dataset with lots Y=0 and few Y=1. I have to run logistic regression, so I'm using a retrospective sample in order to get a more balanced sample. Could someone give me some references that ...
3
votes
2answers
30 views

Definition of $X_t$ in the context of Stochastic process and Time Series

In the book An Introduction to Stochastic Modeling , Stochastic process is defined as : A stochastic process is a family of random variable(s) , $X_t$ , where $t$ is a parameter running over a ...
2
votes
1answer
33 views

Is there any difference between Random and Probabilistic?

It seems i can't directly say probabilistic and random are identical . But this is telling : random experiment is a probabilistic experiment. Is there any difference between Random and ...
-1
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0answers
20 views

Is Experiment and Trial synonymous?

Here they define : When we repeat a random experiment several times, we call each one of them a trial. But here they give the subtitle Experiment or Trial. ...
0
votes
2answers
49 views

Are Event and Outcome synonymous?

Outcome : An outcome is a result of a random experiment. Event : A single result of an experiment. Are Event and Outcome synonymous ?
13
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4answers
944 views

Introduction to machine learning for mathematicians

In some sense this is a crosspost of mine from math.stackexchange, and I have the feeling that this site might provide a broad audience. I am looking for a mathematical introduction to machine ...
0
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0answers
11 views

MSE of training set and validation set for linear regression

The wikipedia article on cross validation http://en.wikipedia.org/wiki/Cross-validation_(statistics) makes the claim that "under mild assumptions that the expected value of the MSE for the training ...
8
votes
2answers
129 views

Citation for Statistical test for difference between two odds ratios?

In a comment here, @gung wrote, I believe they can overlap a little (maybe ~25%) & still be significant at the 5% level. Remember that the 95% CI you see is for the individual OR, but the ...
1
vote
2answers
90 views

asymptotic distribution of a statistic

Say we have iid sample of size $n$ with $X_i \sim Exp(\lambda)$ and the task is to find asymptotic distribution of the statistic $$T_n := \frac{\bar{X}}{s}$$, where $s^2$ is the unbiased sample ...
0
votes
0answers
13 views

Class of semimartingales for which all characteristics can be estimated?

I'm going to ask the question for Ito semimartingales rather than semimartingales in general, but more general answers would be great. An Ito semimartingale is a martingale for which the ...
5
votes
2answers
129 views

$P[X=x]=0$ when $X$ is continuous variable

I know that for continuous variable $P[X=x]=0$. But i can't visualize that if $P[X=x]=0$, there is infinite number of possible $x$'s. And also why do their probabilities get infinitely small ?
0
votes
2answers
75 views

Definition of Time Series

Time series model is defined as : A time series model specifies the joint distribution of the sequence ${\{X_t}\}$ of random variables. For example:$$P[X_1\le x_1,\ldots,X_t\le x_t]$$ for all $t$ and ...
1
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0answers
20 views

What are the best empirical studies comparing causal inference with experimental, quasi-experimental, and non-experimental techniques?

The Issue: People attempt to draw causal inferences using many different statistical techniques (e.g. regression, propensity score matching, regression discontinuity, instrumental variables, etc.). ...
1
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0answers
9 views

Is there any research that compares Likert scale questions to “satisfaction” scale questions?

I'm trying to put together a questionnaire for measuring employee satisfaction with an internal process. I'd like to figure out if there is reason to prefer: ...
3
votes
0answers
51 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 ...
1
vote
3answers
39 views

Inference about parameter $\theta$ be same?

Let $\mathbf x$ be a sample point and $T(\mathbf x)$ be a statistic of $\mathbf x$. Similarly, let $\mathbf y$ be a sample point and $T(\mathbf y)$ be a statistic of $\mathbf y$. In the book ...
6
votes
3answers
187 views

Transformation of Random Variable - Normal Distribution

Let $X$ be one observation from a $N(0,\sigma^2)$ population . What is the distribution of norm of $X$, i.e., $|X|$ ? My attempt : $$f_X(x;0,\sigma^2)=\frac{1}{\sqrt{2\pi ...
0
votes
2answers
95 views

Introductory multivariate statistics reference for beginners

I am from computer science department doing research in data mining and image mining. I remember the last course about stat was introductory to statistics and probability in general. Now I have this ...
1
vote
0answers
14 views

What is the difference (if any) between 'harmonized' and 'standardized data?

I am trying to describe the process of combining multiple datasets into a common format - e.g. a single database that enforces a common vocabulary, scale, and structure. However, I am unclear if I ...
3
votes
0answers
55 views

Proof of Kolmogorov-Smirnov test

Could someone provide me a reference, preferably a book, where I can find detailed proofs and explanations of the Kolmogorov-Smirnov test (including the two-sample variant) and the derivation of the ...
6
votes
5answers
310 views

Recommendation for linear regression with least squares book

I watched several videos on linear regression, mainly from Khan Academy. As I have no background in statistics, I thought this was a good way to get an idea of the topic. However I'm currently writing ...