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Questions tagged [log]

The tag has no usage guidance.

0
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1answer
40 views

Interpretation Confidence interval including zero

I'm performing a negative binomial regression (xtnbreg in Stata). However, I found that the confidence interval of my regression includes zero. I have no clue how ...
0
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0answers
37 views

Interpret GLM log link coefficients

I am currently doing a college assignment in which I have a GLM model in the gaussian family with a log link. I would like to know what the impact per variable is. I know how to calculate the ...
0
votes
1answer
25 views

Is it correct to do stats in log transformed metabolomics data?

I have a dataset from targeted metabolomics analysis, the units I am working with are ng/ml[creatinine] (I use creatinine concentration to normalize the data since the samples are urine and can have ...
0
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1answer
15 views

Interpret log-linear with dummy variable

I have the following model: ln(y) = b0 + B1 X1 + B2 ln(X2) + B3 X3 My X1 is a dummy that can take the values 0, 1 and 2. The coefficient for the dummy 1 is -0,500 My question is how do i interpret ...
0
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0answers
24 views

How to interpret coefficient when the dependent variable is a percentage change?

I am having some trouble interpreting my regression output. My model is LN of transaction volume = alpha + $\beta_1$_RER + control variables RER is defined as the change in the average exchange rate ...
0
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0answers
11 views

Interpretation of log(1+x) variable with y in percentage

In std regression analysis, I'm wondering what the correct interpretation of a log (1+x) variable is when my y is in percentages. My x variable takes on values from 0-4, with the the majority of the ...
2
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1answer
233 views

what is the log of the PDF for a Normal Distribution?

I am learning Maximum Likelihood Estimation. Per this post, the log of the PDF for a normal distribution looks like this: $$ \log{\left(f\left(x_i;\,\mu,\sigma^2\right)\right)} = - \frac{n}{2} \log{\...
1
vote
1answer
41 views

Is a linear correlation between logs useful for making predictions with a regression model?

As I mentioned in a previous question, I have two variables which seem to show a strong linear relationship between the logs of the two variables, even if there is no clear relationship between them ...
0
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1answer
23 views

Log transformed data

When you log transform data what is being tested on the original scale of the data? And why can we use our log transformed data to answer our scientific question? We are looking at data comparing ...
19
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5answers
2k views

What is the intuitive meaning of having a linear relationship between the logs of two variables?

I have two variables which don't show much correlation when plotted against each other as is, but a very clear linear relationship when I plot the logs of each variable agains the other. So I would ...
0
votes
1answer
69 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
24 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
vote
1answer
454 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
30 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
votes
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
57 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
votes
1answer
208 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
votes
2answers
92 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
votes
2answers
114 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
10 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
51 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
396 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
35 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
38 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
30 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
52 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
50 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, ...
2
votes
1answer
583 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
103 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
75 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
vote
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
39 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
1k 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
475 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
536 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
35 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
418 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
80 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
25 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
32 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
1k 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
39 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
98 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
14 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
18 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
47 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
90 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
81 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 ...