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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7 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 ...
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1answer
30 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 ...
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42 views

3 or, even, 4 parameter distributions [on hold]

I have some statistical data for which the pdf has what I think would usually be described as two inflection points. To model this I'm thinking I need something other than the common 2-parameter ...
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1answer
34 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 ...
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3answers
47 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 ...
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1answer
35 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 ...
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1answer
28 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
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1answer
84 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 ...
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1answer
82 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 ...
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0answers
15 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 ...
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0answers
29 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, ...
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0answers
7 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 ...
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1answer
46 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 ...
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1answer
20 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 ...
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1answer
32 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 ...
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0answers
38 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 ...
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0answers
41 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 ...
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1answer
64 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.
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2answers
83 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 ...
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1answer
18 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 ...
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0answers
16 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 ...
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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.
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0answers
14 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 ...
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0answers
18 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 ...
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1answer
67 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. ...
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0answers
59 views

Is it possible to use several interaction terms?

I came across this equation when I was reading the article: $$\textrm{Y} = \alpha + \textrm{X}_1 (\beta_0 + \beta_1 \textrm{X}_2 + \beta_2 \textrm{X}_3) + \varepsilon$$ At least, I can understand ...
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1answer
35 views

Dependence of Error: Does it matter for data-driven models?

Linear regression assumes that the errors of the response variable are independent of each other. Lets assume that a data-driven model like a random forest or multi-layer perceptron is trained/formed ...
2
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0answers
37 views

How good is my computer aided diagnosis system vs the expert?

I have developed a systematic method that attempts to quantify the amount of disease present in medical images. E.g. % area abnormal. In my dataset, I have healthy people with no disease, and people ...
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0answers
38 views

The infamous cross device identification and how to go about it

I am trying to work on a cross device user identification problem wherein I have mobile data,that is apps visited and mobile attributes; as well as browser data via cookies, that is websites visited ...
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0answers
7 views

Finding the ratio of value factors in telecom

Before reading this i know the question i asked can be answered based on our strategies, but i'd like to know the methods of quantifying these strategies into numbers. I'm doing subscriber profiling ...
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0answers
13 views

Modeling complex mechanism with regression (or similar method)

There are six variables A, A', B, C, D, and D' and they are related as shown in the figure below. I want to know the effect of A on C through B. I firstly thought to use 2SLS, but since A and C are ...
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0answers
18 views

Comparing probabilities of two predictive models

Someone has already asked this question. But it is not answered. I have 10 logistic regression models for 10 different product categories. Then i need to come up with the best product to be offered to ...
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1answer
52 views

Disadvantages of uncertainty in modeling

I am preparing a presentation, my work mainly concentrates on uncertainty and sensitivity analysis. I was wondering if I can convince my audience by the importance of studying uncertainty in modeling. ...
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0answers
70 views

Linear Mixed model with lmer in R. How to formulate the within subject factors?

I would like to know which of these formulas is better for answering my research questions (see below) and explain why, or maybe someone can suggest me another one. ...
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0answers
14 views

Complicated joint distribution with constraints on the ratio

I'm trying to create random draws of pairs of numbers based on desired distributions of the numbers and the ratio of the two numbers. Let me explain in more detail, although I apologize if my notation ...
0
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0answers
13 views

How to calculate the probability of a sample to get a specific pattern, given all samples and features?

I have a data aggregation tool, which collects information on many samples (clusters of molecules in this case). So it can create a sparse matrix of NxM binary values (N answers of 0 or 1 for M ...
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0answers
32 views
0
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0answers
12 views

Allocation of product with ANOVA or something else (?) in R - what direction and tests to use?

Assuming a very simplified view of my data looks like this: ...
2
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1answer
23 views

Statistical Modeling with the combination of two models

I'm having a modeling problem now. Assume we have discrete random variable Y and continuous random variables X and Z. First, we assume a logistic regression between Y and Z.(Assumption One) Also, we ...
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0answers
34 views

About the appropriate regression model

I have a quantitative dependent variable and all my explanatory variables are qualitative (binary or multi-category). I need to analyze the impact of each level on the dependent variable. I also need ...
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0answers
39 views

Which estimation technique should I use?

I have time series of six variables from 1973 to 2012, where poverty head count ratio (HCR) is taken as dependent variable. Consumer price index, GDP growth rate, population growth rate, revenue ...
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2answers
95 views

Regression multiple customers per month

I have a file with sales for one complete year. Multiple customers, month number and total sales (per customer): ...
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0answers
37 views

Is my Sales growth dependent on Commissions/Discounts and how do I analyze this in R?

We are capturing sales data by time series (Month by month). Some of the items have commissions and some have discounts and others have both commissions and discounts. Is it commissions or discounts ...
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0answers
9 views

Seasonality in Modeling Population

To conquer the effect of seasonality in data, it is recommended to take multiple sample windows, with each having equal performance window. Question - Should we discard seasonality faced sample ...
2
votes
0answers
38 views

Smearing estimate for cubic root transform in linear regression

I am building a cost model with cubic root transformation of the cost. Hence dependent variable is (cost)^(1/3). Now, am at a stage where i need to re-transform the predicted value to the actual cost. ...
1
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0answers
19 views

Number of candidate inputs that can be handled by different modelling techniques

Am I correct if I say that some modelling techniques can handle better a larger number of candidate inputs? (If we hold the number of observation constant). Let's say I put around 60 different ...
0
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1answer
36 views

Best way to combine information from different models

I have 3 models using different methods for the same outcome and predictor variables of a training set. I can apply these models to a new test dataset for predicting outcome variable. Is it a good ...
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0answers
29 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 ...
4
votes
2answers
347 views

How can the “anti-correlation” between these two curves be shown?

I'm looking at data defined on a given feature with respect to two measures. Whilst both measures are defined on the same domain, both measures are defined on different ranges, so, with a view to ...