A statistical model is a formalization of relationships between variables in the form of mathematical equations. The model is statistical as the variables are not deterministically but stochastically related.

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Model checking versus posterior predictive checks

I am interested in knowing if there are any difference in modeling checking versus posterior predictive checks in the Bayesian framework. Are posterior predictive checks a type of model checking?
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Temporal Data set

I have a fishery data set of fourteen years in a tropical region. This kind of information is quite rare in ecological studies.The data were monthly collected and the set has 2 annual gaps and a gap ...
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23 views

Choosing the correct anova model

How does one choose the best model based on ANOVA's result? I mean I have 3 model outputs 1st is linear+all interaction, 2nd is linear+pair wise interaction and 3rd is linear and I am asked to choose ...
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8 views

Back propagation of Uncertainty

I am recently working on the subject of uncertainty. I read that uncertainty analysis and sensitivity analysis are important topics in this domain(the first is ti do a forward propagation of ...
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12 views

How do I model chapter-verse references?

Context: I am part of an 8-person group in which each person posts a Bible verse every day. For those who don't know, that is of the format "Psalm 30:1" where first we reference the chapter, then the ...
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12 views

Are these models nested?

Are a standard Gaussian and a skew Gaussian nested? I'd say yes, because when we set the skewness parameter $\alpha=0$ in the skew normal we get the standard Gaussian. Also, are the normal/skew ...
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114 views

Other unbiased estimators than the BLUE (OLS solution) for linear models

For a linear model the OLS solution provides the best linear unbiased estimator for the parameters. Of course we can trade in a bias for lower variance, e.g. ridge regression. But my question is ...
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12 views

ordinal dataset modeling [closed]

I need to come up with acceptance criteria (95 or 97% interval for individual population values) for a process that is characterized by an analytical test for one of the components that results in ...
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1answer
28 views

compare time series data with ODE simulation

The same experiment was performed for 4 different initial conditions $(j=1,2,3,4)$. For each initial condition, there were 3 repetition $(i=1,2,3)$ of the experiment. I have 4 sets of data: $X_{ij} = ...
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35 views

Limitations of ensemble selection from libraries

Question related to the approach in Caruana's paper: "Ensemble Selection from Libraries of Models" (linked below) http://www.cs.cornell.edu/~caruana/ctp/ct.papers/caruana.icml04.icdm06long.pdf Seems ...
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2answers
59 views

How to Balance my Dataset?

I have 90% negative examples and 10% positive examples,(13,000 observations, 90 Variables). my model shows me that the miss classifications error is 0.1 but my confusion matrix shows me that the TP ...
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15 views

Are these logical variables for predicting among train/test sets?

I'm wondering if the following makes sense for a model. I have a training and a test set. I want to predict whether a website visitor is a bot or a human, based on several visits. The data has been ...
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20 views

Model Error bars

I have actual observations and estimates from a model (power-law fit). I want to add error bars (+-1 Standard Deviation) to the estimated points. I tried excel and R, but I am not able to calculate ...
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5 views

Developing cross validated regression model (nlinfit) in matab [migrated]

I am using the following code to fit a cross-validated non-linear regression model. ...
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22 views

In a EI RxC model, how can I incorporate additional external information?

I'm fitting an ecological inference RxC model, such as described by the Rosen et al. (2001) paper and implemented by the EI R package. I'm estimating voice transfer from the first round to the second ...
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29 views

Correction for Log normal distribution

Context: I have observed continuous data $\boldsymbol{O}$, for each observation $i$ I have an assumed known $\sigma_i$ for each observation I have an expected model value $E_i$. $E_i$ was produced ...
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13 views

Model Performance - Accuracy not significant but Kappa is?

I am comparing an SVM model to a logistic regression model. When I run a comparison between these models, I get the following output: Accuracy: SVM vs Logistic: p=0.7882 Kappa : SVM vs Logistic: ...
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1answer
46 views

Seeking assistance with model formulation in a simple problem

I'm attempting to devise a mechanism by which gifts or rewards are distributed to players based their location (an area is divided into regions and I can compute if a player is within a region). I ...
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21 views

Selecting proper Linear Model with interaction considered

Data consists of Temp(3lv Factor), Water(num), Fert(num), and Growth(num). Considered model is LM with DV: Growth, IV: Temp with Water and Fert as covariate. Fitted 2-Factor ANCOVA (Full Model) and ...
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25 views

P value validity

I have done a statistical analysis in DNA methylation data, I already wrote my report, but it got rejected by my adviser as he wants me to do some changes in the paper. One question I couldn't answer ...
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25 views

Improving randomForest model

I have following data and code to create a model with randomForest with 80% of rows as training set and 20% as test rows: ...
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1answer
29 views

Recommend monograph on statistical model misspecification

Is there a good book on statistical model misspecification in general? It should cover, for example, the behavior of estimators (e.g., maximum likelihood) when the specified parametric family does not ...
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1answer
137 views

How to improve this logistic regression model

I am using following data and self-explanatory code to create a model for prediction of 'low' (low birth weight) from modified birthwt dataset. I am using 80% for training and 20% for testing: ...
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main effects only significant when modelled with an interaction [duplicate]

model = lm(m ~ xy + a + a2 +y) With an interaction (xy) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -1.8840405 0.9174444 -2.054 0.0404 * x 1.3610892 ...
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How do I choose the correct model for a regression? [migrated]

So the central question of my project is to what extent does a country's level of export contibution towards GDP (i.e. exports as a % of total GDP) affect its GDP growth. I'm comparing this ...
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20 views

Is ıt possible to fit a proportional model by hand?

I was asked to solve the question below by hand as a homework. I did it in R, but I think it is impossible to build the model by hand as one needs to conduct numerical analysis to obtain the betas. Am ...
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reference for regime shifting models [migrated]

I'm looking for a good introduction to regime shifting models. It would be nice to see things like simple example of regime shifting models, ways to detect a regime shift in data, fitting regime ...
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39 views

Regression with dependent variable which ranges from -1 to 1

I performed a series of Pearson correlations which give me as expected values between -1 and 1 (actually very few below zero). I'd like now to see if some factors are linked to these correlation ...
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1answer
45 views

Creating an interaction term with 2 continuous variables: What to do?

I want to create an interaction term in SPSS on two continuous variables (ticket price and household income) in order to use this interaction term in a multiple regression model and test whether my ...
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1answer
34 views

Definition of 'Model Diagnostics'

Can anyone help me out with explaining what the term 'model diagnostics' refers to when applied to multiple regression please? In particular, what tests are necessary to check whether your estimated ...
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11 views

Linear models comparison

I created two linear models to see if a treatment (switching an instrument) significantly affects the relation between two variables. The variables in the model are the same (Concentration ~ Signal), ...
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23 views

How to apply diagnostics to regression model from FactoMineR

Many diagnostics to assess regression models are listed on this page: http://www.statmethods.net/stats/rdiagnostics.html ...
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13 views

How to obtain design matrix for log-linear models?

I need to solve the question below by hand. I think the appropriate log-linear model is $Y_{ij} = \mu + \alpha_i + \tau_j + \epsilon_{ij}$. So, after researching, I realized that I should ...
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15 views

Why is the Multivariate RMSD “normalised” differently to the NMB?

For the multivariate case in regression, and also in other model predictions, the Root Mean Squared Deviation (RMSD or RMSE) is normalised by $n-p-1$, giving, $$RMSD = \sqrt{\frac{\sum_{i=1}^n ...
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1answer
24 views

ANOVA Table for Model In R

I'm trying to figure out how to produce an ANOVA Table in R for a multiple regression model. So far I can only produce it for each regressor, and the Mean Square is calculating as the same as Sum Of ...
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Filling in “gaps” in Sample data from universal data

Quick background - I have a BS in mathematics, and have just recently started a position related to data science (nothing heavy, but requires enough simple statistical analysis that I find myself ...
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1answer
80 views

Fit data to a bivariate function

I want to fit my (x,y,z) data points to a function. You can see the data on Fig.1. The data is symmetric along the main diagonal. To understand my data I have studied (y,z) curves at different ...
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In proc glimmix covariance parameter estimates, what is “scale”? Is it equivalent to residual error?

I conducted data analysis using proc glimmix for my proportional data. Below is the sas code I used and covariance parameter estimates from the output. The experiment was conducted by split plot in ...
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1answer
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Combing Models for different levels of target variable in R

Beginner question please go easy. I have a classification variable with 7 levels. The crux of the problems comes down to the splitting of levels 1 and 2. Below is the output of a random forest in R. ...
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13 views

Question about longitudinal binary datanalysis

I am going to conduct longitudinal binary data analysis on a project since depend variable have multiple outcomes based on different time points. I am familiarly with traditional logit model and ...
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SEM design on dyadic data. Please help!

I have two surveys, and one is implemented to counselors. The questions ask about they feel about their relationship with their administrator. It has have two dimensions, let's say d1 and d2. I have ...
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19 views

Independence of residuals over time

My plots of conditional weighted residuals (CWRES) plotted against time show some sort of time trend (image attached). The response variable is on a Box_cox scale. How could I solve this problem ?
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How to forecast course completion percentage?

The goal of this task is to be able predict percentage of students who registered a specified term which in the future will pass the course. I did a logistic regression for binary response whether ...
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40 views

Why not just use log for regression if it improves r-squared?

theoretical question here: Say I have a model, $y = \beta_0 + \beta_1 x + u$ and it gives an $R^2$ of 0.02 Suppose, I re-estimate the model with $y = \beta_0 + \beta_1\log(x) + u$ which gives an ...
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6 views

Skewed response variable LM [duplicate]

I have a positive asymmetric response variable in a regression model. One of the assumptions about linear model is that the stochastic component of the model is normally distributed. If I have a ...
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15 views

Continuous low truncated response in regression

I can't find a clear answer on how to model a regression with a low bounded response. The tipical case is with response variables that can take only positive results. Poisson and negative binomial ...
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20 views

statistical modelling for imbalanced data

I am dealing with a binary response (good/ bad) type data set of size 2153, which reflects a dependent variable. Out of these, only 67 are in favor of "bad" and the remaining are of "good". Also, i ...
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42 views

Linear Probability Model Construction

I am dealing with a questionnaire consisting of 15 questions. I performed a factor analysis to all the questions and it has given three factors each consisting of 5, 7 and 3 numbers of questions ...
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1answer
50 views

Help constructing a simple regression model with a breakpoint

This is related to my questions here and here. I am still struggling with my model, so I am taking it back to basics. My assertion is simple, I believe that watershed runoff will have a different ...
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Combination Forecast - Which models to pick?

Combination Forecasting can be produced by simply averaging different forecasts or employing more complex techniques (see Makridakis, 1989; De Gooijer and Hyndman, 2006; Goodwin, 2009; Pesaran and ...