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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Find distribution of underling feature

Let's say I have a dataset compose of value for the variable W. The distribution of W doesn't follow any obvious know distribution. I have a model that gives W as a functions of E and K. W = f(E, K). ...
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23 views

What are parametric models? [duplicate]

The term Parametric Models does not sound unfamiliar to me, but I do not exactly know what they are. Can you please briefly explain what model is parametric and ...
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49 views

proving regression with dummy variables gives same estimates as separate models

Let ($x_{i1}$, $x_{i2}$, ..., $x_{id}$, $y_i$), $i = 1,..., n$ be an i.i.d. multivariate sample and furthermore assume each observation belongs to one of possible $K$ categories. Assume for each ...
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1answer
25 views

Calculating spline curve with custom knot positions

I want to fit a spline curve to a simple dataset in R featuring a single custom knot, and extract the resulting models. The data is: ...
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3 views

Calculating Model's Classification Accuracy in R [migrated]

I want to calculate the classification accuracy for a model I am fitting using glmer. Here is what I am doing: ...
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1answer
32 views

Estimates and estimators strict definition

Let's look at a simple regression model: Y = $\hat{\beta0}$ + $\hat{\beta1}$Xi + $\hat{e}$ Estimator's definition is that it's a rule for arriving at an estimate, in this example it would be a ...
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9 views

Can one fuse graphical and quantitative techniques?

The NIST Engineering Statistics Handbook provides a great compendium of graphical and quantitative techniques. Every technique (graphical or quantitative) is usually explained with a set a questions. ...
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1answer
26 views

Statistical model that finds a coordinate (x,y) that minimizes the distance from a group of coordinates

A example would be if I launched a 100 tennis balls in the air and plotted the coordinates of where each landed. I would like to be able to find the point in the center of all those coordinates. I ...
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2answers
182 views

What would be an example of a really simple model with an intractable likelihood?

Approximate Bayesian computation is a really cool technique for fitting basically any stochastic model, intended for models where the likelihood is intractable (say, you can sample from the model if ...
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33 views

Which statistical methods should I be using?

The data is about: a binary variable as response; age; some binary categorical variables (0,1); some categorical variables which have more than 2 outcomes The goal is to find which factors affect ...
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1answer
49 views

Should I just accept that data is strongly not normal when changing families for a Generalised Linear Model has not worked?

I initially tested my data with ANOVA, but upon finding it to be not normally distributed I tried a Kruskal test. This did not make any difference either, so I tried a GLM, taking into account the ...
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33 views

Model selection using AIC in Survival Analysis

As far as I know, the model with lowest AIC is said to be better. However, according to the R output below, the writer says, the model called wei is better, whose ...
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36 views

Linear regression VS linear modeling

Can I claim that linear regression and linear modeling are the same topics? If not, what is the difference? Thanks.
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30 views

What is the “pdm” stat in the “rms” R package?

I am new to the world of Regression in statistics and I have been doing a research in which I am building an ordinal logistic regression model (ORM). In order to fit my ORM model, I am using the 'orm' ...
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33 views

A better fit for sinusoidal data

I have been struggling to fit my data to a sine curve. My data looks like: frame = data.frame(hour = c(0, 1, 2, ... 24), value = (numbers between 0 and 500)) I ...
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22 views

Two-Step estimation

I am currently trying to fit a model that has the following properties: (1) data for several years (2) two decisions/equations (probably involved): (a) one that explains an initial choice of product ...
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15 views

How to plot model with forecasts in R? [migrated]

I recently upgraded R from 2.x to 3.1 and I feel like there were some changes that I am not aware of with regards to plotting models. ...
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25 views

Using A Time Series To “Scale” Another

I know the "average theoretical cost per impression" for Jan 13 - Dec 13. I have other monthly time series for "total # of impressions", "total # of clicks" and "total number of conversions" for Jan ...
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22 views

Calculate pdf of complex model

I'm trying to model the distribution of effects of mutations (let's call it s) in evolution but I'm stuck in generating the probability distribution function (pdf) for my model. So, my model is a ...
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1answer
46 views

How to choose the best logit model using step function in R

I have the data below. I was wondering how I could choose the best model fit of logit model using step function in R. Here is the data in R format: ...
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7 views

Compare model performance to distinguish two groups

I would like to compare a sample from the normal population NP to a sample from an "abnormal" population AP. I have several variables measured on both NP and AP, say age, gender, and VAR1, VAR2 and ...
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144 views

How to summarize knowledge about importance of variables?

Assume that we have 30 features (inputs) each of which can potentially influence the result (output). We try to use the available ("observed") mapping from features to targets to develop a predictive ...
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1answer
20 views

Which models for suitable for integer values of independent and dependent variables

The data set has independent and dependent measurements that are events, and can be counted. What input / output models are appropriate for integer values? So far I've tried linear regression, and ...
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17 views

geeglm not recognizing clusters

I am fitting a geeglm model and it is not recognizing the clustering. my model is ...
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1answer
43 views

graphical representation of fixed effects from lmer

I have run a lmer model in R: ...
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23 views

Adding real zeros to a dataset vs. presence-only modeling?

I have a fisheries dataset for which I have calculated the number of fishing sets in each grid cell (100 km x 100 km) for each month of every year. Fishermen in this fishery are legally required to ...
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14 views

How to decorrelate residuals in r from the covariance matrix

I fit a geeglm model with clustered data and now I would like to decorrelate the residuals of the model in order to run model diagnostics. I read that if I can obtain the covariance matrix of the ...
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1answer
65 views

Are these data underdispersed? If so, what mechanisms may explain this?

Say someone who is well practiced (appears to have reached a performance plateau) shoots 20 free throws on 15 different days and is successful the number of times shown in the upper histogram (...
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19 views

log-linear models and exponential models?

What is usually referred to as "log-linear models"? Is a log-linear model an exponential model where the normalization constant is 1? (since its logarithm needs to be a linear function.) Or is there ...
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25 views

How do we calculate the $R^2$ statistic for a mixed model with one random intercept only?

I have read in previous posts that for mixed models with random intercepts only, the statistic for $R^2$ is $$R^2 = \frac{\text{V of intercept only model} − \text{V of full model}}{\text{V of ...
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1answer
29 views

How do models, parameters, specifications, restrictions and assumptions relate?

So this has been something I've been struggling with for a long time: The specification of a particular model is subjective. However, there seems to be objective ('true') values of the parameters we ...
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21 views

Transformations in Simple Linear Regression [duplicate]

Suppose a linear model for Y in a single predictor var, X. If the residuals show a pattern of increasing variance (wrt X), sometimes a transformation of Y, Y'=f(Y) is considered (where f is sq rt, ...
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23 views

Assumptions on a multiple linear regression model and elastic net

I am interested in using elastic net regression in place of an multiple linear regression. I know when you perform a multiple linear regression you should check the assumptions such making sure the ...
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28 views

How to choose the best regression model?

I have entered main effect terms in Block 1 and interaction terms in Block 2. Based on their beta values, the main effect terms were not significant in Block 1 and the interaction terms were not ...
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23 views

How can I assess if a parametric model can reproduce the same curve with different parameters?

I have a parametric model that I think it is "degenerate" in the sense that I can obtain the same model with different parameters. For example, if I have a convolution of two 1D Gaussians (say, G1 ...
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2answers
260 views

Was this the appropriate regression model?

I was recently proof-reading a friend's thesis (for their writing, not stats usage) when I came across a usage of a regression model which I would regard as incorrect. However, I'm pretty new to the ...
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12 views

Linear model for RCBD

Hi i am told to write a linear model for my stats assignment under an RCBD. ...
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22 views

Do assumptions for estimators affect population parameters?

TL;DR: Specifying a model (a collection of restrictions over a sample space) specifies the model parameters. Specifying an estimation procedure adds additional number of restrictions (assumptions?). ...
2
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1answer
15 views

Repeated measures - sum of biomassproduction

I am student in biology. For my examination I conducted a greenhouse experiment with gras. Actually I am not sure how to develop the correct model and unfortunately I haven't found an answer in the ...
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33 views

Fitting a model to data for prediction - best choice for data

I have some data I need to fit a model to that can be used for prediction (interpolation). The data is summarized by the plot below. The black line is x=y. I want to be able to fit a model so as I ...
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22 views

Model Averaging

Good Afternoon, I am working on model averaging of data collected about bird species and habitat vegetation. I have been using the MuMIn package in R and have taken a subset of all possible models ...
7
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1answer
436 views

Why should we use t errors instead of normal errors?

In this blog post by Andrew Gelman, there is the following passage: The Bayesian models of 50 years ago seem hopelessly simple (except, of course, for simple problems), and I expect the Bayesian ...
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6 views

given a set of pairs of graphs, build a model that accept a graph and predicts it matching graph

Training Data I have a set of pairs of normally distributed graphs, each with a concrete last sample (maximal X) Question I want to build a model (formula) from the data input: a single graph ...
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59 views

How to interpret ANOVA output comparing two models

I'm working with the Blackmoor data from the study "Female adolescents with anorexia nervosa and their parents." I've made 4 models based on this: ...
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36 views

Reverse engineer a predictive model from a time series graph

I have found some real estate plots in a scientific article. These graphs mainly describe, the believes of the author of the development of the real estate market in the future for certain countries. ...
2
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1answer
44 views

Correct numerical result in Bayesian model comparison

I was wondering how to calculate the following Bayesian model comparison. Suppose you have a couple of models: $$M_{1}: x \sim Bin(n, \pi); p \sim Be(1,1)$$ $$M_{2}: x \sim Bin(n, \pi); p \sim ...
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13 views

How to take care of the percentage/rate of an absolute number as independent variable?

I am working on a mixed model, where suppose I have several stores of different sizes. The number of products manufactured in each store is different, say one store can manufacture 100 and other can ...
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1answer
27 views

Definition of Parameters [duplicate]

I imagine this either extremely simple or extremely complex. I am trying to understand the interpretation of the term 'parameter'. A couple of quick online searches deliver an intuitive understanding ...
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13 views

Comparing goodness-of-fit across conditions

I have repeated-measures data. Participants complete both Stage A and Stage B (random ordering). I have two complex models, Model 1 and Model 2, which are fit using optimization techniques. Model 2 is ...
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0answers
19 views

How to measure classification accuracy based on presence only data?

I have a binomial GLMM which I calibrated with data on recreational visits (presence) compared with random controls where no visits were recorded (absence). I generated the controls myself, whereas ...