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Questions tagged [log]

The tag has no usage guidance.

0
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1answer
49 views

skew normal computation

I want to compute probabilities assuming data have log skew normal distribution (in R). As I couldn't find any package that directly computes log skew normal (as plnorm does log normal), I am ...
1
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0answers
23 views

Log results in linear regression

I am just starting working with regression in R. I used some variables and their logs as well in the same regression equation. Unexpectedly, the results show significance of both, variables and their ...
1
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1answer
82 views

Gamma glm log link - what does predicted values mean

Does the predict function in R for gamma glm with log link predict the actual values or the mean value? There is a gamma glm model in R with log link. Using predict(model,data,type = 'response') to ...
1
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0answers
21 views

Sample size for AUC based on mean and SD of raw data

I'm trying to estimate the sample size required to achieve 80% power at a 5% significance level for a superiority study comparing AUC from bioavailability data. My challenge is the only previous ...
0
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0answers
18 views

Log scale abnormaly

I am currently trying to fit my data into an SARIMA model. In order for my data to be stationary, I applied log to it. But when I checked my model fit data, there is an anomaly which messes up my ...
2
votes
1answer
50 views

Computation within log space

What is the conversion of the following equation into log space? $bf2 = 1 + (p * (bf1 - 1))$ Given log.bf1 (log Bayes factor), how do I get to log.bf2 without having to compute bf1, but instead ...
0
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1answer
51 views

Log Transformation in R

I need to transform my not normal distributed data to normal distributed variables. Therefore I need to log-transform them. Log10(x+1) has not worked to create a normal distribution. Therefore, I want ...
3
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2answers
77 views

Unbiased Estimator for $\log\left[\int p(x\mid z)p(z) \, dz\right]$

The naive Monte Carlo estimator is an unbiased estimator for $\int p(x\mid z)p(z) \, dz$, is there a convenient unbiased estimator for $\log \left[\int p(x\mid z)p(z)\,dz \right]$
2
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2answers
107 views

Interpretation of β in case of log-lin model for relationship between X and Y

In many papers, the dependent variable is transformed by taking natural log. For instance, consider the following model: $$\newcommand{\Cov}{{\rm Cov}} \ln(\text{Y}) = \alpha + \beta\, X_1 + \epsilon ...
0
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0answers
8 views

Comparing two Models gained from process discovery

I have a rather basic question on process mining that I however hardly get answered: currently, I do some research on regulated learning in educational/psychological research: I already drew up two ...
2
votes
1answer
47 views

Linear regression - Can I log transform dependent variable and one of the independent ones and keep the rest not transformed? [duplicate]

I have model where my dependent variable is Total money spend and then I have independent variable Income and some other ...
1
vote
1answer
194 views

Computing the Hessian of maximum log likelihood function

I am trying to find the Hessian matrix for the maximum log likelihood function given training data {(xi, yi)} for i=1:N with yi ∈ {+1, −1} for each i = 1, . . . , N for the function: When I try to ...
1
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0answers
29 views

Interpretation on the Log-Lin model with high coefficients

So my model has some high coefficients and i have many doubts how should I interpret them $LnHomii_t = 1.183 - 0.535 LnRendai_t + 4.46\times 10^6Escolai_t - 7.98\times 10^7BOLFAMi_t - 5.378Ginii_t + ...
1
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0answers
33 views

Log-log regression where variables are in terms of growth rate

I would like to estimate elasticity of exchange rate on export. The specification takes the following form: $$Exp=\alpha+\beta_0REER+\beta_1GDP^{p}+\epsilon$$ where, $Exp$ is export growth calculated ...
1
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0answers
13 views

Does log-transform independent variable actually help reducing absolute relative errors in regression?

Based on my experience, I usually log-transform my target variable especially in cases dealing with price prediction. Mainly, it helps with the interpretability. However, I have seen some cases where ...
0
votes
1answer
24 views

Converting relative effect to absolute effect in log model

I have the following model; log(daily sales) = intercept + B1*(event dummy) + error My response variable(daily sales) is basically a daily time series and 'event dummy' is an indicator variable ...
0
votes
1answer
23 views

Log-Log in panel data for multiple regression

I'm using a model, for an article, with 6 independent variables. I used the logarithmic transformation of the dependent variable (Y) and 2 of the 6 independent variables. One of my professors said ...
2
votes
1answer
47 views

In OLS, while using log-log and linear-log transforamtions, is valid to transform some regressors only?

In OLS I was wondering if it is valid to log-transform some regressors only. Specifically, continuous regressors, because it is advised not to transform binary or categorical variables. For instance, ...
1
vote
1answer
314 views

Interpreting adjusted R-squared of a log transformed regression model

I am running a linear regression model where the dependent variable (Y) is log-transformed. I am struggling on how to interpret the adjusted R-squared of this log-transformed model that is meaningful. ...
0
votes
1answer
74 views

Odds ratio, Meta-analysis

I have the following for the data for the meta-analysis: OR , standard errors, logged OR , variance of logged OR I have generated a forest plots first using "OR" with "variance of logged OR" using ...
2
votes
0answers
44 views

Interpreting forecast predictions of log transformed data

Using the forecast function in R, I make a 1-step prediction for a log-transformed data set Y, ( Y = log(X) ). This prediction gives me a mean and a 95% prediction interval. How valid is this ...
1
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0answers
17 views

log model , per capita variabel?

I have a question regarding statistics interpretation . As far as I know when I have two variables I can interpret the results as following: Y and X -- a one unit increase in X would lead to a β β ...
0
votes
1answer
32 views

Interpretation of Regression Coefficients with log transformation [closed]

I am struggling to understand the interpretation of the regression coefficient in a log-log model, log-linear model and linear-log model. To give an example, let's assume that I have the following ...
4
votes
1answer
742 views

How to back-transform a log transformed regression model in R with bias correction

I have created a model to predict the number of people with a certain characteristic (Y) based on predictor variables $X_1$, $X_2$, $X_3$, $X_4$. The model is a multiple linear regression and both the ...
0
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0answers
331 views

Price elasticity in logistic regression with log price

I'm estimating demand and calculating price elasticity using logistic regression. In logistic regression with level price, elasticity is $$ \alpha*price*(1-share)$$ while if one uses log of price, ...
4
votes
2answers
513 views

Is a distribution still considered right-skewed if the majority of responses are zero?

i have a distribution in which the majority of cases take the value of zero and then there are a few (perhaps 10%) with values of 1,2 or 3. would this distribution still count as right skewed even ...
0
votes
1answer
34 views

Does taking logs to supress hetroskedasticity only work for the dependent variable?

I have been told that by logging variables in a regression that hetroskedasticity of errors can be reduced. Is this the case also if only my dependent variable is logged?
0
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0answers
333 views

R-squared for glmmTMB with beta distribution and logit link

I'm looking for a method or function for computing R² for glmmTMB models with a beta distribution and a logit link. I am interested in a ratio (%) response in a repeated measures design. I looked ...
1
vote
1answer
61 views

Is log-log model considered to be nonlinear?

I am currently revising a paper, in which I tested an empirical model in the following form: , where EP is indicator of environmental performance, FDI - foreign direct investment which is the main ...
0
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0answers
17 views

Can natural log transformed variables used in probit models and if so how are their coefficients to be interpreted?

i have several log-transformed continuous variables in my model and want to estimate their impact on likelihood of sale. can i include (natural) log transformed variables in a probit model? if so how ...
0
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0answers
21 views

when should log explanatory variables be used?

I'm modelling auction revenue on eBay against a set of continuous explanatory variables. when is it best to regress against the log of these variables? i understand that it allows you to discus ...
0
votes
1answer
29 views

Does it make sense having scale and log transformed variables to select models?

I have several data to work with in order to select models. Some of the predictor variables vary from 0 to more than 2000 square meters(Area). And some goes from 200 to 800 meters(Altitude). Others ...
0
votes
1answer
727 views

linear probability model interpretation

I have a question regarding the interpretation of a log independent variable in a linear-probability model. For example: I have $\log(GDP)$ as my independent variable and the coefficient is 0.35. Can ...
0
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0answers
18 views

Back transform the integral of a log-log model?

One of my colleagues has an issue with back transforming the integral of model back to its original units. His model has a log transformed Y as a function of a log transformed X predictor. He can ...
0
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0answers
76 views

Is this usage correct for using isometric log ratio [ILR] transform with counts data (compositional)?

If one wanted to construct a simple pairwise correlation matrix from an compositional data table using an ILR transform preprocessing step, would this usage violate any assumptions with the transform? ...
0
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0answers
13 views

How to interpret log(ratio b/w 2 variables) coefficient in a regression framework?

I am struggling to interpret the coefficient of an independent variable in OLS regression equation. The (simplified) equation is of the form: $\Delta Y = \alpha + \beta \ln(\frac{GDP_{2000}}{GDP_{...
0
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0answers
16 views

Interpretation of log log model [duplicate]

I have following equation that i working with log(y)=1+log(x1)+log(x2)+Dummyvar(0/1)+error My question is how do we interpret coefficient of Dummy variable? In ...
1
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0answers
44 views

Is log based transform comparable across groups with different minimum values?

I have data for different groups that includes positive, negative, and zero values. Here is an example: group1: c(-503583,-395833,0.1,3835,19,-0.001,0,48400883) group2: c(-39,-8340,-10,0,0.1,2889,93,...
0
votes
1answer
64 views

Transform Heavy right tailed data

I am clustering (K-MEANS) a data 1.7million observations, which displays a heavy-tailed distribution when examined by plot. What is the best transformation to correct it. does log can handle this?
0
votes
1answer
70 views

Interpreting dispersion for Inverse Gaussian GAM (log linked)

After reading Wood (2006), Zuur et al. (2009) and all questions related to GAMs here, I still haven't found the following: Should I calculate the dispersion for an ...
1
vote
0answers
41 views

Unbiased estimators of the log odds

In the book of Lehmann and Casella (2003) page 83, a random variable $X$ is distributed according to the binomial distribution $Bin(n,p)$, $n$ the number of trials and $p$ the success probability. ...