0
votes
0answers
2 views

Imputation for regression model

i am a student and currently working on a dataset of 2000 records and using sas enterprise miner . i need to do regression analysis to predict payment(target variable) to motor insurance company. in ...
0
votes
0answers
6 views

Restricted Maximum Likelihood (REML) Estimate of Variance Component

Let, $$\mathbf y_i = \mathbf X_i\mathbf\beta + \mathbf Z_i\mathbf b_i+ \mathbf\epsilon_i,$$ where $\mathbf y_i\sim N(\mathbf X_i\mathbf\beta, \Sigma_i=\sigma^2\mathbf I_{n_i}+\mathbf Z_i \mathbf ...
2
votes
1answer
13 views

To implement Bayesian methods on Apache Spark

I was reading the book Bayesian Methods for Hackers by Cameron Davidson-Pilon. He use PyMC for examples. As an experiment, I created a PySpark App with the code example Inferring Behavior from ...
0
votes
0answers
6 views

Regression with fixed effects versus Multilevel Model?

In short: I wonder when I would ever want to use a multilevel model as opposed to a linear regression with appropriate structure. In detail: When I look at Wikipedia, I understand that multilevel ...
1
vote
0answers
8 views

Binary outcome estimation from n “measurements”

Assume you have a binary parameter $y$ which is either $0$ or $1$, and have $n$ measurements $\tilde{y_k}$ of it, each with a different probability $p_k$ of being correct (equal to $y$). With ...
0
votes
0answers
4 views

Reference for forecasting nonstationary variables

My goal is to extrapolate / forecast data up to 10, 20, 100 years depending on certain independent variables. Is there like a publication or a book that I could follow that specifically pertains to ...
0
votes
0answers
3 views

Interpreting and reporting CFA results (localized areas of ill fit indicated by MI)

According to Brown (2015), one is expected to examine and report localized areas of ill fit (e.g. modification indices (MI)) as part of the model evaluation. I have a number of questions about ...
0
votes
0answers
7 views

Threshold cointegration

I have a panel data N=45 T=25. Engle-Granger test confirms co-integration between two I(1) variables. I would like to test for threshold cointegration between these two vars. Is there a user written ...
0
votes
0answers
6 views

Finding the correct model to infill streamflow data gaps

I have 15-minute streamflow observations for a small stream, but the dataset has some gaps in it. I want to fill the gaps with a regression using observations from a nearby stream (and quantify the ...
0
votes
0answers
10 views

Optimize starting parameters for Bayesian Linear Regression?

I'm using PyMC3 in Python 3 and I'm not sure exactly how to optimize my starting parameters. I'm using the regression dataset ...
0
votes
0answers
11 views

Detect an indecomposable distribution through its Laplace transform?

I would like to decide whether a random variable $X$ is an indecomposable distribution. In this situation $X$ is obtained from real-life measurements - say $(x_n)_n$ - so it's not a particular closed ...
1
vote
1answer
15 views

Relationship between categorical factors

I am not sure what this is called in English, but if we have two categorical factors, we can say that one of them (A) is finer than the other (B) if it holds true that if two observations belong to ...
0
votes
0answers
7 views

Parameter Estimates and redundancy

I was wondering if someone can help report the finding on this table. I'm so confused with my Exp(B) being so high and theme nations being redundant. Thank you
0
votes
0answers
11 views

Sample size for testing an output distribution

Please excuse the lack proper mathmatical notation. This is mostly from intuition about the underlying logic. Given a function $f(x)\rightarrow$ A or B randomly The function should return a ...
0
votes
0answers
10 views

Intuition behind using Noise Contrastive Divergence in Neural Language Models

I am going over this paper [https://www.cs.toronto.edu/~amnih/papers/ncelm.pdf] which uses NCE to avoid dealing with the normalization constant of a log bilinear model, when maximizing the likelihood. ...
0
votes
0answers
5 views

How to translate theorem into R code properly? (ruin probability of a discrete-time bi-risk model) [migrated]

We're having trouble with the realization of this theorem (recurrence relation for estimating ruin probability of a discrete-time bi-risk model). Basically, here you can see the theorem itself with ...
0
votes
0answers
8 views

categorical weighted vector

I have 4 variables Each variable is an ordered categorical variable The range of values for each variable is ...
1
vote
1answer
10 views

Detecting a difference in the direction of two groups of vectors

I have two groups of patients, one group obese, one non-obese. I have vectors representing the longitudinal axis of the kidneys in each patient. I am comparing the orientation of the right kidneys ...
0
votes
0answers
5 views

Conflicting results between GLMM and Post-hoc lsmeans

I'm studying the effect of pH and cross-types on mortality of fish. Treatment is categorical (2 levels: control and low pH) and cross-types is also categorical (4 levels: parents wild male x wild ...
1
vote
0answers
27 views

Hierarchical linear modeling of Brinley plot data

My question pertains to using hierarchical linear modeling / mixed modeling using lme4 in R on Brinley plot data. I have experience with R, but no experience with HLM, and limited experience with ...
0
votes
0answers
9 views

Is there an Equivalent of “proc surveylogistic” in R?

A colleague told me about "proc surveylogistic" in SAS -- see details here -- is there an equivalent function in R?
0
votes
1answer
13 views

Probability distribution on a subset of a simplex

I want to define a probability distribution on a subset of a simplex. for example, on a 3-simplex, we know that $x_1+x_2+x_3+x_4=1$ and $X \sim Dirichlet$. Would it be possible to constraint $X$ more ...
0
votes
0answers
6 views

How to assess the significant level of a sample difference per number of element

I have 3 samples of 28 paired elements which have been tested for normality and they are not normal due to biomodal distributions. I carried out a Friedman test and is not significant. However I know ...
5
votes
4answers
120 views

Should I use an average to summarize ordinal data?

I need to work out a "average" (for lack of knowing a better word) of ratings or perhaps I could call them labels. Basically, I have a list of words that have been rated 1 - 3 for difficulty. 1 being ...
0
votes
0answers
9 views

Neural Network - Learning accuracy drops heavily after a couple of epochs

I designed a neural network to classify some images into 28 classes. Here are the parameters : Weight Decay : 0.005 Momentum : 0.01 Learning Rate : 0.001 and 0.005 Learning Decay : 1 Input : 100x100 ...
0
votes
0answers
11 views

How to update latent discrete variables in MCMC?

Most of the discussion on Bayesian model with latent variables that I've seen fall into two classes: continuous latent variable underlying the observed discrete outcome (e.g. probit model (Albert ...
1
vote
1answer
21 views

Heteroskedasticity Question

I have a model that's affected by Heteroskedasticity: bptest(m1) studentized Breusch-Pagan test data: m1 BP = 65.055, ...
1
vote
1answer
9 views

Regression Using Surveys with Unequal Number of Responses

I am trying to figure out how to properly do regression analysis on a data set from a peer-review survey where individuals in the survey have an unequal number of responses. Below is description of my ...
0
votes
0answers
8 views

Generalized model with different kinds of variables

I'm working with captive jaguars behavioral data to answer how several independent variables affect the incidence of a certain behavior "E". My dependent variable is the number of times the behavior E ...
2
votes
0answers
20 views

Logistic Regression: Should I include a non-significant variable that notably increases the OR of a significant variable?

I am studying the effect of different pollutants on the probability of a genetic mutation. My binary logistic regression models are as follows: Model 1: Dependent variable: genetic mutation (binary ...
0
votes
0answers
7 views

How many parameters required to approximate quadratic function with NN

How many layers do you need to build a RELU network (1-layer or deep) to approximate x^2 function on [0,1] with 1e-6 accuracy. What is the practical result on the same, say with Tensorflow ...
0
votes
1answer
12 views

How to compare total effect of three variables across two regressions that use different subsamples?

I am running the following regression in Stata on two sub-samples (Low and High groups): \begin{equation} \begin{split} {ln(1+New\:co-investors)}_{i,t} = \alpha_0 &+ \alpha_{1}PreSuccess_{i,t-1} ...
0
votes
0answers
4 views

Equal Error Rate (EER) and Receiver Operating Characteristic (ROC) curve

I have a one-vs-all classifier set. This set consists of, let's say, 3 classifiers (LibSVM SVMs) each trained on data for a class and all other class data. The current setup for a sample is that the ...
4
votes
0answers
28 views

Estimating a variable from its cosine corrupted by additive Gaussian noise

I observe $y_i=\cos(\theta)+z_i$, $i=1,\ldots,n$, where each $z_i\sim\mathcal{N}(0,\sigma^2)$ is an i.i.d. zero-mean Gaussian random variable. I am interested in estimating $\theta\in[0,\pi]$ with ...
3
votes
2answers
39 views

Robust methods and penalized regression

Are penalized regression methods such as ridge or lasso sensitive to outliers? If so, what options are there in regards to robust methods for penalized regressions and are there any packages in R?
2
votes
0answers
13 views

Confidence Interval for Regression Line (simple linear regression)

So I've constructed a confidence interval for my regression line. However, because I have 2500 data points it is a very, very narrow interval (I can barely see it next to the regression line when I ...
2
votes
0answers
12 views

SVM optimality criterion in Bottou, Lin (2006)

My question relates to an alternative optimality criterion for an SVM dual solution derived in Bottou, Lin (2006) in pages 8 and 9. Let: $\alpha^* = (\alpha_1^*,\dots,\alpha_n^*)$ be a dual ...
0
votes
0answers
12 views

Significance across Categories of Quantitiative Data

I have a quantitative independent variable that has been grouped into categories (A-G). Example: Age of people by decades (20s, 30s, 40s, etc.) I want to determine if the difference between the ...
0
votes
0answers
7 views

Anova output in R when testing lm() [duplicate]

I am trying to make a simple linear regression to see if my variable "totalssq" has an influence on my variable "hadsa". (my data is "dstatss") Both are quantitative. I made a model with lm() and ...
0
votes
0answers
5 views

A conceptual question about LSTM-RNN

I am working on series prediction by LSTM-RNN. In the training stage, I use a random series (white noise ) as input to go through a system and get the output. LSTM is implemented to learn the ...
0
votes
0answers
8 views

How can I calculate ± estimate based on sample set?

Say I have 25M weights on a population of 100M. Say the average weight of the 25M random sample is 150lbs. How can I be more precise in describing the average weight of the larger 100M population? In ...
0
votes
0answers
12 views

Interpreting regression Output for CAPM

I have an interpretation problem. As you can see below there's a linear regression output for the CAPM. I don't know how to interpret the significance level. ExIndex has a very low p-value, but the ...
1
vote
1answer
10 views

Supervised learning on symmetric vectors

I have a simple question: Let's say I'm applying the supervised learning method LVQ to a labeled data set in order to train a classifier. This data set contains feature vectors $x \in \mathbb{C}^N$ ...
-1
votes
0answers
21 views

Converting from strings to factors in R [on hold]

I am having a problem converting from strings to factors. This is my code and in it is how I tried to convert from strings to factors. ...
0
votes
0answers
7 views

SPSS data management [on hold]

grateful for any help! Here's the background: I'm using SPSS In my data, each row is an individual's appointment Each row has an identifier for the individual (SSN) Some rows have demographic data ...
0
votes
0answers
14 views

Estimating SEM models with more than one endogenous variable

I have a panel data set with two rounds. I am using two equation structural model where my endogenous variables are $y_1, y_2, x_1$ and $x_2 $ and my exogenous variables are $ z_1$ and $z_2 $. ...
3
votes
0answers
15 views

Decomposition of SARIMA models

I use R for time series analysis. I would like to evaluate decomposition algorithms. decompose and stl from "stats" package lead ...
0
votes
0answers
5 views

Why would Conversions and Conversion Rate not correlate strongly?

Do any of you know, or have thoughts about, why website Conversions and Conversion Rate would not give a strongly correlating r-value (pearson)? When analysing some data I'm getting r-values of around ...
0
votes
1answer
12 views

'moderator' analyses in a meta-analysis

Sorry if I use the wrong terms here, I am still learning how to do this. I am conducting an meta-analysis comparing two treatment types, using Cohen's d. I have completed the primary analyses of the ...
0
votes
0answers
2 views

marginal structural model and partial least square regression

I have a question about the time varying exposure (air pollution) Let say I have data on PM10, SO2, and O3 during time period T1, T2, and T3; and the outcome at T4. And I want to assess the ...

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