A statistical model is a formalization of relationships between variables in the form of mathematical equations. A statistical model describes how one or more random variables are related to one or more random variables. The model is statistical as the variables are not deterministically but ...

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3
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1answer
84 views

Model selection, issues of judgement

I have a general question on model selection strategies in regression models. In my research, the main goal is rarely prediction but almost always estimation of effects of certain variables. I have ...
0
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0answers
14 views

Understanding my serial mediation from R and creating a serial mediation model

I am having trouble understanding my serial mediation results from R. I think that my results are significant, but I'm not sure how to create a model using my results. Can R create the model on its ...
0
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0answers
10 views

Can it be as accurate to model child-variables to estimate a parent-variable instead of modeling the parent-variable directly?

With time series data, let's say you want to model the return of the S&P 500. Could you get as good or better results by modeling each stock, and aggregating them to estimate the return of the ...
2
votes
1answer
58 views

Difference Between Discrete Time Proportional Hazards and Logistic Regression

My data consists of one row per person, per month that person was "exposed" to an event. So the month is the discrete time and the row corresponds to one "person-month". There are a few independent ...
0
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1answer
14 views

Making a mob-like decision tree with pre-specified splits and models for leaves

I would like to make a special kind of hybrid tree model in R, similar to the mob models in the party and ...
0
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0answers
17 views

How to analyse the influence of 100 categorical or continuous predictors on one continuous response?

I am analysing a genetic dataset that consists of 288 individuals, 100 genetic markers as predictors and one continuos variable (day of death) as outcome. Each predictor has three categories or ...
1
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0answers
26 views

Checking Cox model assumptions with multiple imputation

I have run multiple imputation using MICE. I would now like to run a Cox model on it (using with,pool), and make sure that is justified. That is, I need to make sure that the proportional hazards ...
0
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0answers
10 views

Using one model to validate another? (Validation with no ground truth?)

My question is on model validation when there is no ground truth. Suppose I have a data set of attributes: $x = \{x_1,\ldots, x_n\}$ These attributes are different attributes that describe animals ...
1
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1answer
21 views

dangers of averaging between model approaches

I am working with some ridership data that is broken down by route, year and month. I have built and tested a whole bunch of models ranging from GLM, GEE, GENLIM, and Panel and ARIMA data models. I ...
3
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0answers
40 views

How to model and predict a user's preference by their click-through history?

I am trying to model my users' food preferences so that I can recommend restaurants which he/she might be satisfied. The following is some sample data: ...
0
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2answers
44 views

Response Surface Methodology (RSM) for A Mathematical Model

I would like to create a second order polynomial model using Response Surface Methodology (RSM) for a non-polynomial mathematical model. For example, I would like to represent $f(x)=x_1 + \sin(x_1x_2) ...
0
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0answers
23 views

Bayesian inference and a logistic weight control problem

Currently I have a lot of problems to select which I want to work on. For some I already got ideas on how to solve it. However, I haven't dived deep into Bayesian inference so far but, from what I ...
0
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0answers
18 views

Statistical/ML models when observations have different amounts of input

Let's say we're predicting an employee's performance review score for the following year based on his/her performance review scores from each previous year of their employment. We might have these ...
2
votes
1answer
62 views

CART with Ordinal Response Variable using rpartScore Stuck

I'm trying to fit a decision tree over some data which has ~40K rows and ~200 features. The response variable, y, is ordinal and takes values ...
0
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0answers
16 views

How to construct the right model(s) for a specific problem

I recently started as a data guy in a medium sized company. I have background in mathematics (and computer sciences). Unfortunately and on the other hand luckily, I'm the only and first one in the ...
0
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0answers
27 views

delta function as the likelihood in Bayes theorem

I am reading a paper which is doing a MAP estimation on the following model: $$ \phi_t = \max_k p(\phi_w|\phi_t) p(\phi_t) $$ So we are seeking $\phi_t$ which maximizes that joint distribution. ...
1
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0answers
55 views

Fitting one set of data with two functions

I have a set of data (42 points): ...
0
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0answers
7 views

Comparing LOESS with PBSpline

Penalized B-Splines and Loess both allow creating a continuous function from your data. In many cases they are quite similar, but sometimes they differ significantly, for instance for the below ...
2
votes
1answer
24 views

I have two sets of data, what is the best way to fit one set of data so it most closely matches the other

I have taken two sets of data with two different instruments. We know data set A taken with instrument A is very accurate and precise and that set B, while precise, is not accurate. Thus my data sets ...
0
votes
1answer
18 views

Data analysis using Gross vs. Variation Data

I am trying to find a macroeconomic model that fits my data mainly using simple multiple regression. However, I am a little confused with the mistakes I may be doing. The question below might sound ...
0
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0answers
10 views

Correct or most valuable way to model consumption/usage among users of a product or system?

Is there a best method for approximating average daily consumption among users of a product? I'll use an example to illustrate. We have monthly data for the past year (we have all data since launch) ...
0
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0answers
12 views

A general approach to getting around model packages which cannot handle rank deficiency

A few packages which employ variations of generalized linear models (pscl and VGAM), specifically the functions ...
0
votes
1answer
29 views

Missing data and covariate analysis

I'm working on a model which has been fitted to longitudinal data (using mixed effects regression). I'm also investigating the effects of about 6 covariates on this model. Covariate A (continuous ...
0
votes
2answers
74 views

Why are SVMs hard to fit?

I often hear the following complaint from people: "SVMs work really well WHEN they actually work." By "work" I mean that the algorithm will actually finish running. Are SVMs difficult to fit in ...
0
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0answers
17 views

Detecting Gibbs Sampler convergence with Raftery and Lewis Diagnostic

Hi! I'm trying to understand and implement the Raftery and Lewis Diagnostic for detecting the number of iterations required for a gibbs sampler but cant seem to understand the formula. ...
1
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0answers
18 views

Understanding changes in bookings per medical practice

I have data for counts of bookings per day. I have data for counts of active medical pracitces per day (active means that they have published appointments that are able to be booked in the past 28 ...
-1
votes
1answer
34 views

Is statistics is the same as mathematical modeling or is it about sophisticated guessing of a pattern between the data? [duplicate]

"Is statistics is the same as mathematical modeling" or "is statistics about sophisticated guessing of the relationships between the data" or "is it meant to create a pattern between the data"? Which ...
1
vote
1answer
36 views

What is the origin of squaring centred data as way to model variances instead of means?

I recently came across this Answer by @mpiktas wherein he suggested a transformation of $y_i \rightarrow y_i^{\prime}$ $$y_i^{\prime} = (y_i - \overline{y})^2$$ followed by fitting a model for ...
0
votes
3answers
60 views

Relationship between price and quantity in R

I tried to figure out how I can analyze this project. To find out how to analyze relationships between prices and quantities. I think with only two variables you can't build models. For example, one ...
0
votes
1answer
39 views

Regression model for edge-sensitive data set

I have data sets in which important information is allocated in the edges, which are also very sensitive to inaccuracies. I would like to find a regression model based on edge recognition that brings ...
0
votes
1answer
48 views

Dealing with zero-inflation if the data are not count data type

In the literature I found that for the count data with a lot of zeros so-called zero-inflated distributions (models) and so-called hurdle-at-zero distributions (models) could be used. The differences ...
3
votes
1answer
118 views

Multiple ARIMA models fit data well. How to determine order? Correct approach?

I've got two time series (parameters of a model for males and females) and aim to identify an appropriate ARIMA model in order to make forecasts. My time series looks like: The plot and the ACF ...
1
vote
1answer
101 views

Determining order of ARIMA model using Box-Jenkins. Correct approach / argumentation?

I obtained a couple of time series from estimating my (mortality-)model which I now aim to forecast with an appropriate ARIMA(p,d,q) model, which should be chosen with the use of the Box-Jenkins ...
1
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0answers
16 views

Extracting amplitude information from sum of two step functions

Background: I'm looking at power information from a circuit powering multiple freezers, resulting in a signal that is the sum of two step functions, with slightly different frequencies. I'm looking ...
0
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0answers
33 views

Building a Predictive Model

I'm inexperienced and confused in statistics, so I need help. I have a data table, values are temperature, particulate matter(PM), and vegetation indexes. And idea is that when PM increases, ...
0
votes
0answers
9 views

Finding a joint distribution of a large dimension

This is a rather soft question. I have data samples that are definitely pairwise correlated, and possibly correlated in higher order. It is of dimension $50$, and I am looking to describe it via some ...
0
votes
1answer
55 views

Structural breaks, stationarity and time series modelling

This is a simplified version of my problem... Say I have two time series ($X$ and $Y$) and I know that $Y_t$ is somehow dependent on $X_t$ but not on $X_{t-k}$ for any $k > 1$. Ultimately I want ...
1
vote
1answer
22 views

Model selection in the classification problem with costly information

Let's assume we have a $X_T$ matrix of $N$ variables and $Y_T$ available for training a model to solve classification problem for variable $y$. Normally, we can use all $N$ variables for training and ...
0
votes
1answer
35 views

What to do with important features?

I am currently solving the titanic problem in kaggle. The data of the problem consists of several features such as "sex", "class in society", etc., and you are to predict whether a person survived the ...
0
votes
0answers
44 views

ARIMA models for mortality modelling (Box-Jenkins methodology)

Fitting the Lee-Carter model of mortality to data provides a time series for the period-related effect, which is subsequently often modelled as an ARIMA(p,d,q) process in order to make forecasts. p,d ...
0
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0answers
68 views

List of nlme models

I am trying to find a list of models that nlme provides. I am completely new to this area and finding it hard to get a comprehensive list of models that nlme provides facilities for. I have tried to ...
-2
votes
1answer
65 views

What property of logistic regression is useful for modeling user behavior? [closed]

I want to know that what property or attributes of logistic regression make it to useful for modeling user behavior.
2
votes
2answers
94 views

How to model the problem of predicting failure in Server Clusters

The problem goes as follows - There is a cluster of Servers. Whenever there is failure/anomaly in any of the server, a report is logged. Some of the features of the log report are Time of Failure ...
1
vote
1answer
24 views

Comparison of time series models

I'm trying to create a model for a series $X = \{X_1, X_2, ...\}$. I don't assume that the $X_i$ are identical distributed nor that they are independent but at least that they have something in common ...
1
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0answers
18 views

Interpreting an apparent inconsistency - fitting regression models on subsets suggested by an interaction

Say we learn a linear regression model with three continuous predictors $X_1$, $X_2$, and $X_3$ (along with interaction terms $X_1X_3$ and $X_2X_3$), for some variable Y. The fitted model suggests a ...
1
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0answers
17 views

Lognormal and radial

Is lognormal distribution a class of radial distribution? P.S Gaussian, truncated Gaussian are all classes of radial distribution.
1
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0answers
22 views

On the difference between parameter driven models and observation driven models

Could I have an explanation on what are parameter driven models and what are observation driven models as categorized by Cox (1981) in Statistical analysis of time series: some recent developments ...
1
vote
0answers
19 views

The score of a dynamic model is a martingale difference sequence

I am going to write down some parts of Dynamic models for volatility and heavy tails by Andrew Harvey (2008) with my comments in bold and then ask for an alternative explanation of the final part. ...
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0answers
11 views

Modeling Disaggregation

I'm going to try to explain my problem as simply as possible, but if there's any clarification needed please let me know. Essentially, I'm predicting that I'm going to sell 100 units total across 5 ...
0
votes
1answer
99 views

Why the discrepancy between the classic definition of contrast and that in R

According to Wikipedia, contrast is defined as follows: Let $\theta_1$,$\ldots$,$\theta_t$ be a set of variables, either parameters or statistics, and $a_1$,$\ldots$,$a_t$ be known constants. ...