0
votes
0answers
2 views

What probability distribution to use for a variable X for which only an estimate is known?

I assume that... X must be in the interval (0,1). The estimate given is the expectation of the unknown distribution. Would it be possible to somehow average over all distributions on (0,1) that ...
1
vote
0answers
3 views

Logistic regression gives very different result to Fisher's exact test - why?

I have a confusing situation where I have strongly conflicting results from two ways of analyzing my simple data. I measure two binary variables from each participant, AestheticOnly and ChoiceVA. I ...
0
votes
0answers
2 views

Mixed and random effect model with multiple crossed random effects in lme4 vs nlme

I am trying to fit a few models as follows for my data of observations recorded from $p$ genotypes planted in $n$ locations for $m$ years. The aim is to estimate BLUPs finally. $$Y_{ijk} = \mu + G_i ...
-1
votes
0answers
10 views

How to store multiple predicted values in R

I have the below code which is throwing error .I need to store multiple prediction arrays so i'd finally have pred1 ,pred2,...pred99 ...
0
votes
0answers
6 views

How to analyze personal time series

I have a time series data of multiple subjects' performance over the time as well as time series metric of their mouse movement. In other words, for every subject, there are two graphs: Performance ...
0
votes
0answers
4 views

Conditional vs. Unconditional Maximum Likelihood

I have some questions on the difference between conditional MLE (CMLE) and unconditional MLE (UMLE) in practice. In what follows I will only talk about the unconditional and conditional mean and leave ...
0
votes
0answers
3 views

Factor analysis using “outliers-only” time series

Some background I run a factor analysis of a time series $Y$ using a standard OLS model with n+1 independent variables $(F,X_1...X_n)$, where $F$ is the main factor (from an explanatory power ...
2
votes
0answers
6 views

GMM estimation of linear regression with intercept restriction

Say I have a time series regression as follows: $$y_t = a_i + \beta_i x_t + \varepsilon_t^i \ \ ; \ \ t = 1, 2, \cdots, T \ \ \text{for each } i$$ Now say I impose the following restriction on the ...
0
votes
0answers
7 views

Absolutely continuous probability distribution and its probability density

In the wikipedia article, it states: "A random variable $X$ has density $f_X$, where $f_X$ is a non-negative Lebesgue-integrable function... $F_X$ is the cumulative distribution function of $X$... ...
0
votes
0answers
9 views

Fuzzy regression (using lp)

I want to replicate a fuzzy regression using a linear programming problem approach. I have the following information: " A fuzzy regression analysis with only one independent variable X results in the ...
1
vote
2answers
25 views

Why there is no significant difference between a number list and its 100 times list

I am finding that there is no significant difference between a number list and another list which has 100*same numbers. The P value is 0.4487. The means are obviously very different (100 times). Why ...
0
votes
1answer
10 views

Vector Error Correction Model (VECM) vs. Dynamic Factor Model (DFM)

Two questions regarding the equivalence (or lack thereof) of vector error correction model (VECM) and dynamic factor model (DFM): Can every VECM be expressed in an equivalent DFM representation? Can ...
0
votes
0answers
4 views

Using interaction terms in an MCMCglmm

I am using MCMCglmm models in R, with hierarchically nested data. The basic structure of the data is as follows - each dyad is a unique combination of focal/other: ...
0
votes
0answers
9 views

What is the difference between ZCA whitening and normal whitening?

I am confused about ZCA whitening and normal whitening (divided the feature vector(obtained from PCA) by sqrt of eigenvalues obtained from PCA). As far as I know, x_ZCAwhite = U * x_PCAwhite, where U ...
0
votes
0answers
4 views

MCMCglmm interpretation of effective sample size

I'm running a selection of MCMCglmm models in R, and have a basic question about the outputs. Based on what I've been reading, one indication that the model is mixing well is a large effective ...
0
votes
0answers
4 views

what's the difference between MMSE estimation and MAP estimation

can anyone answer the question regarding difference between minimize estimation error and minimize wrong estimation? Thank you
0
votes
0answers
7 views

Standardizing Responses on an Ordinal Scale

I'm looking at a data set where items originate from three sources (A,B,C). A number N of survey takers grade some items from sources A,B, and C with a few categories, all on a Likert 1-5 scale. The ...
0
votes
0answers
13 views

Asymmetric Error Bars

My question is about the application scenario of asymmetric error bars and how to calculate different positive and negative error limits in error bars. I know in symmetric error bars, we can calculate ...
1
vote
0answers
12 views

Pattern recognition with time series analysis

I'm looking for some good pointers to pattern recognition with time series. Possibly something practical that can be easily understood. As a toy example, think about collecting data from an ...
0
votes
1answer
39 views

Simple Linear Regression…?

So let's suppose that the normal error regression model $Y_i = \beta_0 + \beta_1X_i + \varepsilon_i$ is applicable except that the error variance is not constant; rather the variance is larger, the ...
0
votes
0answers
12 views

Linear Combination of Random Normal Variables

In order to prove that the linear combination of two independent normal distributions(say Z=X+Y) is normal, i am using their MGFs to show that the linear combination also has a similar mgf. This works ...
0
votes
2answers
9 views

Clustering objects based on event timestamps

I have data for $n \approx 500$ objects, and for each observation I have between ~50 and ~200 observations. Each observation consists primarily of a timestamp when an event happened (and includes some ...
0
votes
0answers
10 views

Correlation coefficient in case where dependent variable cannot be larger than independent

I am trying to fit a linear correlation to data. Normally, an obvious choice would be Pearson's R^2, but in this case that over-estimates the accuracy of the data because the dependent variable can ...
0
votes
0answers
12 views

How come Z-test is recommended by some for analyzing A/B tests?

I've been researching the deep underlying mathematics of A/B testing. I understand A/B tests to be Bernoulli trials (conversion / non conversion) and categorical data represented in a 2x2 contingency ...
0
votes
1answer
11 views

Discriminating for early detection of problems

I could (please) use some suggestions on how to tackle an issue that has been brought up where I work. When a new product is launched, our company tracks how many AND what type of replacement parts ...
0
votes
0answers
22 views

Why are Coefficient of each other principal component cannot be all of the same sign?

For the covariance matrix $\Sigma \in \mathcal{M}_{p,p}$, a positive-definitie (non-singular) matrix with its elements $\sigma_{ij} >0$ for all $i,j = 1,2,...,p$. How do I prove that the ...
1
vote
1answer
7 views

Predict after using Box Cox Transformation

I am doing a Multiple Linear Regression on a data set where: The response variable is continuous One of the explanatory variables is continuous and the rest are binary(categorical) 1 if it is there 0 ...
4
votes
1answer
34 views

Proof that the coefficients in an OLS model follow a t-distribution with (n-k) degrees of freedom

Background Suppose we have an Ordinary Least Squares model where we have $k$ coefficients in our regression model, $$\mathbf{y}=\mathbf{X}\mathbf{\beta} + \mathbf{\epsilon}$$ where $\mathbf{\beta}$ ...
0
votes
0answers
8 views

How can I make decisions from the output of predict.coxph()?

I'm studying Survival Analysis for the purposes of customer churn modeling. I've managed to put together a model, but I'm confused about what to do with the output. As I understand it, the output is a ...
0
votes
0answers
16 views

Why is this probability statement true?

I'm reading the proof to a martingale central limit theorem. In the statement of the theorem, we assume that $\eta^2$ is an almost surely (a.s.) finite random variable. In case I, they wrote, ...
0
votes
0answers
6 views

Relevant Population [on hold]

A poll is to be conducted in which 2000 individuals were asked whether the election petition of the 2012 election was fairly conducted. The 2000 individuals were selected by random digit dialling and ...
2
votes
0answers
9 views

average difference between two sets of values

I've been keeping track of my car's gas mileage by calculating gallons divided by miles traveled. The car itself calculates this mileage as well, but its values are always a little higher than the ...
0
votes
0answers
7 views

Mean of vectors minimizes L2-norm [duplicate]

Recently introduced to data mining and am trying to understand how the mean of vectors minimizes L2-Norm/Euclidean distance. I've tried googling it and can't seem to find a proof as to how something ...
1
vote
0answers
7 views

Using min leaf size above 1 in random forest/treebagging

Are there any advantages in using a min-leaf-size above 1 in classification with bagged trees(/random forests)? I would imagine that it could make the classification more robust as some area in the ...
0
votes
0answers
10 views

Recursively computing Dirichlet cdf.

I want to implement the Dirichlet CDF and I wonder if I can compute it recursively Following Frigyik et al., we know that if $Q \sim \text{Dir}(\alpha)$, then: $X_1 \sim \text{Beta}(\alpha_1, ...
1
vote
0answers
13 views

Formal definition of thin-tailed distribution in terms of regular variation, etc.?

Use a standard definition of slowly-varying as $$ \lim_{z\to\infty} \frac{L(t x)}{L(x)} = 1, \forall t>0 $$ Define a fat-tailed distribution with CDF $F(z)$ as: There exists an $\alpha > 0$ and ...
0
votes
1answer
26 views

model selection through shrinkage (Lasso) using glmnet

I would like to use model selection through shrinkage (Lasso) using glmnet. After trying the example of the glmnet manual and tried the procedure with my data. ...
0
votes
2answers
24 views

Why is the intersect negative and what does my regression show

I am trying to get my regression right. I want to see, if subs increase how much increase in revenue is seen. The dependent variable is Revenue while the independent variable is subscribers. Least ...
0
votes
0answers
11 views

Impute missing values using aregImpute

I have a data frame with 61 columns. Some data is missing. I read in Steyerberg's book about aregImpute in Hmisc. I used it with ...
0
votes
0answers
21 views

Influence of information on price

How can I check if some market information affects price(or rates)? For example, I have discrete time series of price and I know moments, when the market gets new information. Which model should I ...
0
votes
0answers
11 views

Multivariate regression with 3 dependent variables and only 1 independent variable?

I need to compare the marginal effect of one independent variable (X) in 3 different dependent variables (Y). I did a multivariate regression using Stata commands manova and mvreg, but I am doubting ...
0
votes
2answers
21 views

How to report a linear mixed-effects model equation

I have run a linear mixed-effects model, with one fixed effect (dd) and a random slope and intercept term for individual (fInd) and would like to know how to report the results? In particular, I would ...
1
vote
0answers
3 views

Comparing proportions when measurements are an average over other measurements (MTBF)?

Set up We have a few types of items. For each item, a failure occurs randomly at some time $t$ after start. We take $n$ measurements of $t$ for each item type, and we do this for all items. The ...
1
vote
0answers
33 views

Distribution for $Y = \sqrt{X_1^2 + X_2^2}$, when $X_1, X_2$ are dependent and normally distributed with different variance? [duplicate]

Is there a closed form distribution for the transformation given by $Y = \sqrt{X_1^2 + X_2^2}$, when $X_1, X_2$ are jointly normal but dependent random variables with different variance? OBS: I know, ...
1
vote
2answers
31 views

WLLN: can expectation exist but be infinite?

WLLN: Let $\{h_i, i = 1, \dots n\}$ be an $m \times q$ sequence of iid random variables with mean $\mu = E[h_i]$ that exists and is finite. Then $1/n \sum_{i = 1}^n h_i \rightarrow \mu$ in ...
0
votes
0answers
11 views

confidence interval for aggregated expectation from logistic regression

My model steps: 1.I fitted a logistic regression model $Y\sim X$; 2.then get the probability $P(Y=1)$ for each record; 3.then I summed the probability $R = \sum_i(P_i(Y=1))$ to be the expected return, ...
0
votes
0answers
16 views

Where to read about how to build a calculator like this one

I am wondering how to build a sample size calculator like this one: http://www.evanmiller.org/ab-testing/sample-size.html Will the intro chapters of a stats textbook cover this? I've taken a couple ...
1
vote
0answers
12 views

How does one adjust for data snooping when using ACF and PACF?

ACF and PACF are routinely used for approximate identification of a time series model, e.g. as described here. Say, one takes a look at the plots and guesses that it's something like ...
0
votes
0answers
19 views

Connection between Lasso formulations

This question might be dumb, but I noticed that there are two different formulations of the Lasso regression. We know that the Lasso problem is to minimize the objective consisting of the square loss ...
3
votes
0answers
21 views

How does the 45 degree banking rule apply when plotting multiple data series in one chart?

Cleveland's rule of thumb that the average slope of a line should be 45 degrees. But what about when a chart plots multiple data series? Is there a generalization of Cleveland's rule, or do you set ...

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