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0
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1answer
33 views

Interpreting Log-Transformed Percentages in OLS

In a log-log model, such as $\log(y) = b_0 + b_1 \log(x)$, I know that with OLS the standard interpretation is a "1% increase in x is associated with a $b_1$% increase in y." I have three related ...
4
votes
2answers
75 views

Approximation of logarithm of standard normal CDF for x<0

Does anyone know of an approximation for the logarithm of the standard normal CDF for x<0? I need to implement an algorithm that very quickly calculates it. The straightforward way, of course, is ...
0
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0answers
16 views

A few questions about using logarithms in regression equations [duplicate]

I have a simple regression equation where log(salary) = b0 + b1*log(sales). How would you interpret b1 in this model?
-1
votes
1answer
27 views

Why can certain variables in a multiple regression not be included in logarithmic form?

I have a multiple regression equation where log(salary) = b0 + b1(ceotenure). What is the purpose of putting the dependent variable in logarithmic form? How would you interpret the change in y for a ...
1
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0answers
26 views

What to do with coefficients of log-transformed predictors in meta regression of effect sizes?

I am preparing data for a meta-analysis regression of effect sizes, in which I will study the determinants of effect size for a specific variable across several studies. I have some studies in my ...
0
votes
1answer
67 views

Log and natural log

I have few seemingly simple questions. I am working on time series data and applying vector error correction model. I find different results when I transform the data into LOG and LN. Which one is ...
1
vote
0answers
35 views

Metropolis Hastings when acceptance rate is not a probability

I need to implement a Metropolis Hastings where the acceptance probability $\alpha$ is not a probability but a logarithm of a score. The logarithm of a score is a negative float. In original ...
0
votes
1answer
50 views

dealing with exponentials in python - infinities and overflows [duplicate]

In a machine learning algorithm that I'm using, I need to get the exponential values of something in one of the steps. This is the step that I'm dealing with right now: I've already got all the ...
1
vote
1answer
33 views

Regression and link function

Suppose we have $E (\log (Y)) = a+bx $ vs $\log (E (Y)) = a+bx $. Can $\exp (b) $ in both cases be interpreted as a geometric mean?
1
vote
1answer
33 views

Log-scaled chart for visualizing extreme range

I need a simple bar chart or the like. I am not a statistician by any means, but this chart is supposed to accurately represent FileIO in MB/s compared to the theoretical peak of a specific drive. ...
1
vote
1answer
53 views

Understanding stationarity with Inflation

I am looking at the link between inflation and insolvencies for an econometrics project. I have the raw quarterly insolvency data and raw quarterly CPI data for the UK (roughly 100 samples) from ...
2
votes
2answers
118 views

Reporting regression statistics after logarithmic transformation

I'm a bit troubled about how to report linear regression statistics after log transformation of the dependent variable. I suppose I should report the transformed coefficient, but would they be easily ...
0
votes
0answers
23 views

What is data augmented by the additive inverse?

I am reading Biclustering of expression data (Cheng and Church, 2000) The paper is about the Cheng and Church biclustering algorithm and its main metric, the mean squared residue (MSR). It is said ...
1
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0answers
28 views

Use of log of an independent variable and its implications

I am currently analyzing the relationship between Google Search frequency and the CDS market. I used a monthly backward rolling regression to determine the 30 search queries which have the biggest ...
2
votes
1answer
137 views

Interaction term in a linear log model

I am using a linear-log model to test whether overseas development assistance and remittances positively affect FDI in cases of good governance and financial market development. Let's say I want to ...
0
votes
1answer
39 views

Expectation operator and logarithmic function

$$\frac{1}{C_t}=E_t\left[\beta \frac{1}{C_{t+1}} \right]R_{t+1}$$ How to log linearise the function? $C_{t+1}$ is the stochastic term; $\beta$ is known.
4
votes
0answers
62 views

Avoiding large variances when taking the logs of small values

I have two random variables $(X$ and $Y)$ that are always positive. The assumption I'm making is that their logs follow normal distributions (i.e., $N(\overline{\log(X)},s^2_{\log(X)})$ and ...
1
vote
1answer
76 views

interpreting the coefficient on a logged independent variable from a probit model

I am using a double model with log transformed independent variables and have calculated average partial effects. Now I am now not sure how to interpret the coefficients; particularly those from the ...
0
votes
1answer
69 views

Best way to estimate a regression with reaction times

I have reactions times in a no-normal distribution, so I am using logarithms. Which can be the best way to estimate a regression? Later, I would like to plot the results according to the age of my ...
1
vote
0answers
69 views

Linear-logarithmic Regression in MATLAB with two input arguments - which model to assume?

Look at the following plot and ignore the solid lines please (just look at the dotted/dashed ones). ONE curve is described by the following parameters and ONE fixed value for the second input ...
7
votes
4answers
2k views

Is it correct to use 'Ln' instead of 'ln' for natural logarithm?

In some research papers, authors use 'Ln' for natural logarithm instead of 'ln'. Is it correct?
2
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2answers
134 views

Use logarithmic or linear values when performing correlation and ANOVA?

The data was collected using a logarithmic scale: scores (explanatory variable) are collected with values from 0-5. A score of 3 is 10x the value of a score of 2. I wasn't sure if using either the ...
1
vote
0answers
52 views

Log Transformation in Growth Mixture Model (Mplus user)

I am using parallel process growth mixture modeling to estimate bidirectional longitudinal dynamics between pain (0-100 theoretical range of values) and sleep measures (0-20 theoretical range of ...
0
votes
1answer
99 views

Interpret interactions and logarithms in linear regression

I'm currently playing around with linear regression in R, and I've come up with a regression that fits data quite well. I'm just having some problems with interpreting the coeffiecents of my model. I ...
0
votes
1answer
106 views

Doubt in derivative of logarithm

This seem to silly but I wanted to confirm if the derivative of the log-likelihood $\hskip 2 pt l(x_i)$. The derivative of $$\frac{d (\sum_{i=1}^{M} log(x_i))}{dx} = \frac{1}{x_i} \sum_{i=1}^{M} ...
3
votes
2answers
132 views

Taking the log of variables

Just before I start the question I would like you all to know that I have checked the other threads on taking the log of variables but I still think I have a question that hasn't been touched on yet. ...
2
votes
1answer
66 views

Estimating the effects of cumulative odds ratios - additive or exponential?

I have run some regression models that examine the effect of variable X (a 15 point continuous scale) on Y (a binary variable - not perform/perform a particular behaviour) using logistic regression. ...
4
votes
1answer
44 views

Plotting variables in transformed space

Suppose $A = X_1/X_2$ and $B = X_3/X_4$. Why would one plot the data in $(\log A, \log B)$ space as opposed to $(A,B)$ space?
0
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0answers
48 views

How to plug viral coefficient into an exponential growth function?

Is there an exponential growth function that has the viral coefficient(k-factor) as a variable? For example I have 10 initial customers Each invites 10 new customers 20% convert into a new customer ...
0
votes
2answers
81 views

Clarification of log interpretation

Let us say we have this regression $$\ln(y) = a + B_1(age) + B_2\ln(savings) + B_3\ln(income+1)$$ When carrying out the regression we obtain: $$\ln(y) = 0.3445 + 0.5(age) + 0.4556 x_1 + 0.55566 ...
3
votes
1answer
120 views

Performing calculation of a product of a sequence,

I have performed a calculation that a sample of records will contain at least 1 defective record assuming replacement. There are 20,000,000 records in the population, 7,000 are defective, and I will ...
0
votes
0answers
71 views

Akaike criterion for gaussian mixtures

I am trying to estimate a multimodal gaussian mixture model with an unknown number of nodes. I wish to use a model selection strategy and iteratively test whether incremental modes leads to ...
2
votes
1answer
103 views

Questions on equation of log linear regression

I have been asked to check over a paper. The paper is using log linear regression. In the following log linear equation, $x$ is the dependent variable, $y$ is a continuous covariate, $z$ is a ...
1
vote
1answer
464 views

Bias correction of logarithmic transformations

I read that there is a bias when we transform a series with a logarithm and then applying the inverse function, but only in forecasts of the mean values. I don't understand what it means exactly. ...
0
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1answer
653 views

Is it valid to log-transform percentages?

My thesis is to examine the validity of the relationship between tourism represented by tourist exports (real growth) and economic growth using a dummy variable and force workers. I tested the ...
0
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0answers
88 views

Variable not significant in log specification

I am estimating a model which gives me significant parameter estimates for my variables of interest. However, when I use the log version of the model log(dependent)=log(independent), I don't get ...
6
votes
1answer
332 views

Binary Models (Probit and Logit) with a Logarithmic Offset

Does anyone have a derivation of how an offset works in binary models like probit and logit? In my problem, the follow-up window can vary in length. Suppose patients get a prophylactic shot as ...
4
votes
1answer
226 views

Why are time-related covariates log transformed in modelling? [duplicate]

I have seen a lot of examples of transforming time-related variables (e.g., age, year, days, etc.), but I don't understand the reasoning behind doing this. I don't think it's for stabilizing the ...
1
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0answers
208 views

When analyzing a difference for log-transformed data, when to take the log?

I am working with laboratory data that needs to be transformed due to skewness. It has been gathered at 2 time points and I am interested in the change from time #1 to Time #2. My question is, do I ...
2
votes
2answers
2k views

First difference or log first difference?

I am evaluating the effect of covariances between series on returns. That is I run the following regression: $$ r_t = \beta_0 + \beta_1\text{Cov}(Y_t,r_t) + ...$$ I have conducted my analysis with ...
2
votes
0answers
76 views

OLS standard error log log regression

I am estimating the following Power Law relationship: $$\ln(\text{Rank}) = \text{constant} + \alpha \ln(\text{Size})$$ where $\text{Rank}$ is $1,~2,~3,~...,~n$, and $\text{Size}$ is the raw value. ...
1
vote
1answer
332 views

Plotting 0 in a log scaled axis

I have a very large and sparse dataset of spam twitter accounts and it requires me to scale the x axis in order to be able to visualise the distribution (histogram, kde etc) and cdf of the various ...
6
votes
1answer
2k views

Expected value and variance of log(a)

I have a random variable $X(a) = \log(a)$ where a is normal distributed $\mathcal N(\mu,\sigma^2)$. What can I say about $E(X)$ and $Var(X)$? An approximation would be helpful too.
3
votes
1answer
136 views

Can we use as predictor a variable that was used in the calculation of the dependent (a ratio)?

I wonder if someone could give me some advice on using ratios as a dependent variable in a Generalized Linear Model. I have a variable referring to the increase of "size at Time 1" to "size at Time ...
0
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0answers
45 views

What does taking the logarithm of a variable mean? [duplicate]

Possible Duplicate: When are Log scales appropriate? Say you have a bar graph displaying data, for example, "Cost of Computer Orders by Population", and you are trying to analyze the data ...
-5
votes
1answer
103 views

Solving logarithms using variables [closed]

LogQ= a+bLogP+cLogI+dLogPm b= -2.174 c= 0.461 d= 1.909 Determine price elasticity of demand, income elasticity, and cross price elasticity
2
votes
1answer
89 views

multiplicative treatment effects with standard errors

I simplified this a fair bit after finding a draft version of the Imbens and Rubin chapter. I am interested in estimating a constant multiplicative treatment effect from a randomized experiment. I ...
2
votes
1answer
130 views

Fitting ratios in multiple regression formula

I would like to ask a (probably very simple) question with regards to multiple linear regression. I have an experimental formula in the form: $$ Y \sim \frac{a_0 \cdot X_0}{(a_1 \cdot X1) * (a_2 ...
1
vote
1answer
473 views

Logarithmic scale on a plot with negative values

I would like to plot two time-series on a same graph. One series takes much larger values than the other, so I thought a semilog scale might be appropriate (i.e. linear X (dates) and log Y). However, ...
0
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0answers
31 views

Interpret natural log transformed dependent variable [duplicate]

Possible Duplicate: Interpretation of log transformed predictor I have a regression equation (below). In the raw form, my Y dependent variable is in days (length of stay in days). I ...