0
votes
1answer
7 views

What kind of distribution is this via t-distribution

Suppose we repeat an experiment identically and independently 100 times. Each time we construct a 99% confidence interval for $\mu$ via the t-distribution. Let X = the number of times the confidence ...
0
votes
0answers
4 views

Inference with only left-censored data

Suppose I have a data set that is only left-censored data, ex: <5, <5, <5, <10, <10, <10 A technique to handle left-censored data is the Kaplan Meier estimate, see page 5 of ...
2
votes
1answer
13 views

Not sure I understand how R calculates the covariance

Please forgive this silly question, I'm fairly new to statistics. Consider this R code: ...
1
vote
1answer
7 views

Does the estimated overdispersion parameter of Negative Binomial depend on mean

Negative Binomial distribution can be parameterized using mean, $\mu$, and overdispersion $\psi$, so that the variance of NB is $\mu + \frac{\mu^2}{\psi}$. We know there is no analytical solution for ...
1
vote
0answers
71 views

Problem with evaluating if a 2D or 3D point lies in a Gaussian sphere (for implementing a Parzen-window estimation)?

START EDIT I try to formulate it more briefly: I have 2D or 3D sample points in a coordinate system, and want to check which of those points lie within a (bivariate/multivariate) Gaussian ...
1
vote
0answers
9 views

JAGS meta-analysis

I'm using JAGS to run a meta-analysis and I've run into an issue. I have calculated log-response ratios and errors for about 177 studies, where studies fall into one of 8 groups. I'm interested in ...
2
votes
1answer
20 views

Hierarchical Bayesian modeling of incidence rates

Kevin Murphy's book discusses a classical Hierarchical Bayesian problem (originally discussed in Johnson and Albert, 1999, p24): Suppose that we are trying to ...
1
vote
0answers
18 views

Finding an equation with many variables to fit a set of data

I am writing a program which takes notes from a keyboard as the input, (just numbers, 1 to 88) and decides which notes are played by which hand. There are a lot of variables, for example, the position ...
2
votes
0answers
15 views

How to subset alternatives in nested multinomial logistic regression?

I am trying to predict whether or not captains in a particular groundfish fishery choose to fish on any given day and what variables may influence that decision. Originally I had planned on using ...
0
votes
2answers
16 views

SVM for unbalanced data

I want to attempt to use Support Vector Machines (SVMs) on my dataset. Before I attempt the problem though, I was warned that SVMs dont perform well on extremely unbalanced data. In my case, I can ...
2
votes
2answers
52 views

Why we shouldn't be obsessed with unbiasedness

In my Bayesian statistics class, my professor makes the remark that we should not be obsessed with unbiased estimator. First: I understand this statement in the sense of trading biasedness for ...
1
vote
0answers
11 views

Comparing nested, non-linear models

I would like to compare the fit of two non-linear regression models: 1) $$ Y = (\Pi^{10}_{i=1}\beta_i^{x_i})^{1/\Sigma \beta} $$ 2) $$ Y = \begin{cases} (\Pi^{10}_{i=1}\alpha_i ...
1
vote
0answers
14 views

Should I be using a Welch or standard T-test?

I'm really confused here. I am trying to compare two sets of data which differ in sample size. One has 257 entries and the other has 598. They are measures of scores on two different assessment types ...
1
vote
1answer
38 views

Regresssion of Accurate Data

I'm collecting calibration data for a device which involves three variables $S$, $L$, and $x$. For a given coordinate $(S, L)$, the device will provide me with the corresponding value of $x$ to a high ...
1
vote
1answer
39 views

When to use Bayes' theorem to calculate conditional probability?

Given 2 events $E, F$, I know that $P(E | F) = \frac{P(E \cap F)}{P(F)}$. However sometimes the Bayes' theorem is used instead: $P(E | F) = \frac{P(F | E) P(E)}{P(F|E)P(E)+P(F|E^{c})P(E^{c})}$. ...
0
votes
0answers
6 views

ARMA Model Output & Excel

I am using my Eviews Output of an ARMA Model, taking the coefficients in other to perform my Forecasts in Excel. However, I am not being able to match the residuals of the in-sample estimations ...
0
votes
0answers
12 views

Cummulative Mixed Model in R variable names.

I'm trying to fit a cumulative link mixed model clmm() in Rstudio. I'm currently having issues with the diagnosing what is wrong with my model from the output I am getting. The output I got from my ...
0
votes
0answers
8 views

Comparing Overlapping Percentages

I observed how frequently participants exhibited five specific behaviors during testing. The total of the below percentages exceeds 100%, because some participants (30.43% of the sample) exhibited ...
0
votes
0answers
9 views

MC Integration Interval Probability [duplicate]

We were asked this question for homework: B. Use MC integration to estimate the probability that X · exp(X ) < 2.5, assuming that X ∼ Gamma(1.2, 3.7). Details. The PDF, CDF, and QUANTILE ...
6
votes
2answers
74 views

How to properly handle Infs in a statistical function?

Suppose I have a function such like: f <- function(x){ exp(x) / (1 + exp(x)) } it's supposed to work for any real value of x, but actually it returns NaN ...
1
vote
1answer
34 views

Can a machine learning algorithm be evaluated based on a random sample?

I am trying to evaluate how well (or bad) a semi-supervised algorithm is performing on a given dataset. The algorithms assigns one of 10 labels to each data point. The dataset is huge, and it's not ...
1
vote
0answers
5 views

Correlated Random Effects Probit vs. GEE Population-Averaged Probit

My question relates to recent work on correlated random effects probit models (see these slides from Wooldridge) and comparing them to GEE population averaged probit models: Is one approach better as ...
0
votes
0answers
18 views

MAP Estimator with Laplacian Noise

I need to calculate the MAP estimator of $ x $ in the following case: $$ \left [ \begin{matrix} {y}_{1}\\ {y}_{2} \end{matrix} \right ] = \left [ \begin{matrix} x\\ x \end{matrix} \right ] + ...
0
votes
0answers
29 views

Identifiability in linear regression

If we have a generative model: $X_2=X_1a_1+\varepsilon$, where $\varepsilon \sim \mathcal{N}(0,\sigma_2^2)$, do we have $X_1=X_2a_2+\varepsilon '$, where $\varepsilon \sim \mathcal{N}(0,\sigma_1^2)$ ...
0
votes
1answer
68 views

What does the | in |Z| mean in mathematical expressions for distribution statistics

I am doing some self study on statistics and noticed that in the notes that I was using the $|Z|$ expression as attached in the photos below. I am confused with the "$|$" that is being used. The only ...
0
votes
0answers
8 views

which test to use here to test the significance of overlap with respect to a control?

i'm not sure what statistical test to use to compare a scenario like this: I have a list of candidate regions A (560k regions) and I want to know if my candidate regions enrich for a particular set ...
1
vote
0answers
32 views

What to do with missing values?

I have missing values for some of the variables in my data. I am using pooled OLS and have 144 observations. I have missing values for three of the variables. Less than 10% of the data for each ...
4
votes
0answers
20 views

R packages that work with biased samples

I'm working with a biased sample of web users. I'm only able to track responses of users who have navigated my site in a certain way, and I'd like to run an analysis to determine how certain factors ...
0
votes
0answers
8 views

Labelling subplots [on hold]

I have produced a volcano plot, however for an examples sake, let's use : ...
1
vote
1answer
5 views

How to integrate observational errors in goodness of fit tests?

I have an astrophysical non-linear curve, specifically a power spectrum. I need to fit this curve with a model and obtain the goodness-of-fit (GOF). This gives me expected and observed values. The ...
0
votes
0answers
30 views

How does this algebraic relationship among expectations work?

Find the expected mean squares error of lack of fit. Trial: $$SSLOF=\sum_{1}^mn_i(\bar y_i-\hat y_i)^2\\=\sum_{1}^mn_i(\bar y_i-\bar y)^2-\sum_{1}^mn_i \hat\beta_i^2(x_i-\bar x)^2$$ and ...
1
vote
1answer
12 views

Repeated measures tests without “before and after” measurements

When reading about repeated measures ANOVA, until now 99% of examples are always with "before" and "after". But if I understood correctly the point of repeated measures ANOVA is not necessarily to ...
1
vote
0answers
5 views

Evaluate deviation from negative binomial model

I'm trying to figure out how to determine to what extent a sample deviates from a negative binomial model fitted to a larger population. As an example, I generated counts of doctor visits for a ...
0
votes
0answers
5 views

how to measure multichannel distances between “event” sequences

In TraMineR, seqdistmc is used to measure multichannel distances between "state" sequences. I am wondering if there is a function to measure multichannel distances between "event" sequences.
0
votes
2answers
21 views

Cox PH model selection and validation

I am trying to analyze my data using survival CoX PH in SPSS v.19 and also attempting to make different prediction models (without and with a biomarker of interest). I am a clinician (not a ...
0
votes
0answers
10 views

How to can IRT-Models be understood in GLM/ SEM Framework? (Predict Learning with added Paradata-Covariates)

I'll be working with data from an a Intelligent Tutor System similar to one studied in the KDD-Cup 2010 on Student Performance Prediction and plan to use IRT-Models to infer item and ability ...
0
votes
1answer
22 views

Cluster with distance threshold in R

I'd like to get clusters with a maximum inner distance threshold. Now I use hc <- hclust(d) and cutree(hc, numofclasses). ...
1
vote
0answers
33 views

Maximum Likelihood Estimation with Known Parameter Distribution

Consider i.i.d observation vector ${\bf x}$ from a distribution $F$ depending on vector of parameters $\boldsymbol{\theta}$ and single parameter $\alpha$. We would like to estimate parameters ...
0
votes
1answer
18 views

Adjusting significance level with for different kinds of tests (chisq, mann whitney etc.) on the same variable

I have conducted a series of tests on a single, dichotomic variable (presence/absence of a personality disorder in a neurological illness) in order to compare several things (i.e. presence of anxiety ...
1
vote
1answer
32 views

AR(1) on autocorrelated data that is not a time-series

I need to apply a regression model on observations that is not time series data but each observation presents a store and the amount of cartons that gets sent to that store. For instance ...
0
votes
0answers
10 views

Relationship between number of Principal components and Exploratory factors.

Would like to know is there any heuristic relationship between the number of components identified from PCA analysis and the number of hidden factors provided by EFA analysis on the same data set?
1
vote
1answer
39 views

How to model a skewed Student's t disribution

I have a small number of samples (5) of a large population (~10,000). The samples are percentages and hence I know from the context that no answers are possible below 0% or above 100%. From this one ...
1
vote
0answers
25 views

Hammersley–Clifford theorem

I'm reading this paper http://image.diku.dk/igel/paper/AItRBM-proof.pdf and I got stuck in page 4 with equation (1) that's based on Hammersley–Clifford theorem. I'm not good in reading set theory ...
1
vote
0answers
12 views
0
votes
0answers
11 views

Difference in memory usage between gbm and blackboost [migrated]

I'm working on a database with around 250000 observation and 50 predictors (some are factors so in the end around 100 features) and I have trouble using the blackboost() function (from mboost package) ...
2
votes
1answer
19 views

Is it ok to adjust significance level according to number of comparisons in simple correlations?

a referee asked me to "split" the significance level for the number of comparison, although i am not doing repeated comparisons but just spearman correlations between variables. I have set the ...
0
votes
0answers
6 views

Model selection and parameter estimation in forecasting with a Dynamic Linear Model

I am implementing a general purpose prediction tool for time series. I want to tolerate missing values, so I decided to settle for DLMs. To make it as relevant as possible on a large number of ...
0
votes
0answers
14 views

Standard deviation of normalized data

I have a data set $y_i$ with the standard deviation $\sigma(y_i)$ for each value. The $y_i$ represent some value of photon count rate. For some reason, I normalize the data set to the average count ...
5
votes
2answers
72 views

Fitting data sample to a distribution

I'm trying to fit a data sample to a distribution. So far I have created a histogram and fitted the data with a lognormal distribution in R and made a Q-Q plot in excel (of log(benefits paid) against ...
1
vote
1answer
26 views

Dealing with different time series data in Machine Learning

I am trying to create a stock market model based on fundamental variables for the US economy. I am using R. Some of the variables I am looking to include are: GDP, Unemployment Rate, Initial Claims, ...

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