The logarithm of a number is the power to which the base must be raised to get the number.

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-2
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1answer
35 views

Why should I choose features or plot them manually when there are built-in functions to do that?

Why should I select variables due to my intuition if there are builtin functions in sklearn python like SelectKBest() and PCA() If I plot graphs of features of the data to see if they can detect the ...
0
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1answer
21 views

How to interpret a log transformed (x+c)? [duplicate]

I need to use log-log regression and because I have lots of zero values I tried to add a very small constant c=8E-12 to x and it works pretty good. Xs are very small probabilities. lnY= a + b ln ...
1
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0answers
29 views

Estimating elasticity of $y$ with respect to $x$ in a log-log specification

My rudimentary workings so far is that; $\log(y_i/x_i) = \log(y_i)-\log(x_i)$ Factorise, so, $\log(y_i/x_i) = \log(y_i) + \upsilon_i - \log(\gamma_i + 1)$ Thus, elasticity of $y$ to $x$ is ...
5
votes
2answers
107 views

Alternatives to multilevel model with log transformed outcome

I'm working with linear mixed-effects model in Stata. Dataset has three levels of 100k observations, nested in 500 regions, nested in 70 regions. Currently my modelling strategy is to use ...
13
votes
3answers
1k views

In statistics, should I assume $\log$ to mean $\log_{10}$ or the natural logarithm $\ln$?

I'm studying statistics and often come across formulae containing the log and I'm always confused if I should interpret that as the standard meaning of ...
0
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0answers
8 views

Amplitude and confidence intervals using log transformed dependent variable

I have two questions: - I am fitting a cosinor model to estimate the seasonality of vitamin D levels, which is natural-log transformed. Now, I will estimate the amplitude = sqrt((beta1^2)+(beta2^2)), ...
0
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0answers
11 views

Logarithmic transformation and regression for Product sequence

So, I have an equation like below: $k_{A}*A*k_{B}*B*k_{C}*C=f$ (eq1) The only value I have is A,B, C, and f. I want to estimate $k_{x}$ and I have several equation so that I think it is possible ...
1
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1answer
40 views

Modeling a Y~Log(X+constant) equation

I have this data set of Xs and Ys. I am trying to fit an equation to it using R, of the form: y ~ log(x+constant) Any ideas how to do it?
0
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2answers
63 views

Conflicting interpretations for coefficient of log transformed predictor

If you think this is a duplicate, please have a look at the last paragraph. In a regression model where both dependent ($Y$) and independent ($X$) variable are in natural logs, what is the exact ...
0
votes
1answer
20 views

Inverting logarithmic output from VAR model

I'm working on a VAR model and am doing a log transformation of the raw data. x = log(x) After differencing, running various tests and running a VAR(2) model, I ...
0
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1answer
45 views

Why do the predictions of a linear (log-log) model not approximate those of a nonlinear (power) model?

I am having trouble using a linear (log-log) model to approximate the predictions of a nonlinear (power) model. I wish to plot the predictions of the linear model on untransformed axes, and I believe ...
5
votes
1answer
75 views

Find the distribution of $ N = \min \left\{k: \prod_{i = 1}^{k}U_i \lt .6\right\}. $

I'm cross-posting this from math.SE because it's not getting any love over there. However, if that's considered heresy, I can delete the posting over there. The Statement of the Problem: Let $ \{ ...
1
vote
0answers
29 views

Can we take natural log of a variable in ratio form e.g. age dependency ratio? [closed]

I have been through many posts arguing about whether we should use the natural log of a ratio or not. Yet I am still unable to understand the concept completely for I feel even ratios differ from each ...
3
votes
4answers
146 views

How to interpret regression equations with logarithms, based on log difference being approximate to percentage change?

$y = 4 + 2.5\,x + u$ For an increase of 1 unit of $X$ (that is, $X$ to $X+1$), we expect an increase $2.5$ units of $Y$ (that is, $Y$ to $Y+2.5$). Is that right? What if there's a/an $\ln$? ...
1
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0answers
13 views

Trendline for data with two phases

I'd like to know how to fit a curve to a set of data that has two phases. For the below data I've tried using a third order polynomial, but I think that's overfitting the data and I've tried using ...
0
votes
1answer
60 views

Log transform produce sign change on coefficients

I want to regress $x_1, x_2, x_3$ and $x_4$ on $y$. Question: When fitting a regression model in the regular fashion without any transformations the coefficient for $x_4$ is positive. However when I ...
1
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0answers
36 views

How should I deal with a nonlinear objective function in linear programming? [closed]

What I tried: Let $x_i$ be the number of units in compartment $i$. We want to minimise the probability $$z = 0.3^{x_1} 0.4 ^{x_2} 0.2^{x_3}$$ s.t. Space: $$30x_1 + 40x_2 + 20x_3 \le ...
0
votes
1answer
17 views

How to get real value from log adjustement value

I am looking for some data for my research, and found reliable graph which showed the correlation of fetal weight and gestational age which is what I want. However, the weight in that scatter plot ...
3
votes
0answers
64 views

Is there a model with additive effects for always positive dependant variable?

When modeling a dependant variable always positive and continuous, models as log-transformed linear model or GLM with log link are generally used. The log-transformed linear model is : ...
0
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0answers
10 views

If you transform response time data, e.g. to generate a CI, do you transform the values back for interpretation? [duplicate]

I would like to create a CI or highest density interval for response time data. The distribution of the response times is quite skewed and I think about transforming them by LN(y). However, my ...
1
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1answer
25 views

Normality test on logarithmic data

I had to take the log of my data, and now I want to test for normality of my data. Can I use the standard normality tests or do I have to use some special test? I used the ...
0
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0answers
110 views

Back-transform coefficient from linear mixed model with log-transformed response

I ran a linear mixed model (lme4::lmer in R) with a log-transformed (base 2) response, and predictors were not transformed. I want to back-transform my coefficients to make a statement about effect ...
0
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0answers
246 views

Curve Fit with logarithmic Regression in Python

I need to find a model which best fits my data. It's look like this: So I thought about logarithmic regression. But when I try to make a simple fit in python I get the following result: My code ...
1
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0answers
10 views

Multiplicative Measurement Error in Response Variable

I understand that taking log of the multiplicative error model transforms it into the additive error model. Let $y'$ be the observed response variable, with $y$ being the true response variable and ...
0
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1answer
72 views

Log-transforming time series data before cointegration testing

I am testing the cointegration between these variables: Gold Price (Ringgit), Exchange Rate - MYR to USD (Ringgit), Real Effective FX Rate Based on CPI, T-Bill 10 Years Rate, Consumer Price Index. ...
3
votes
1answer
70 views

log-log transformation

I am making a linear regression model for house prices. My data set includes price per square foot of a property and floorspace so I have multiplied them to get the total price of each property. My ...
1
vote
1answer
28 views

Exponential Regression with x outside of exponential

I am trying to do exponential regression by matrix notation, and I am trying to figure out to create my $\mathbf{X}$ matrix to fit my model. I know that I need to use a model function of the form $c_1 ...
0
votes
1answer
37 views

Running Same Regression Across Multiple Individuals

I am trying to run a log log regression of the form LNX ~ LNP, where X = Units Sold and P = Price (in reality, I would have a number of other variables included in the model). The data is retail ...
1
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0answers
25 views

Alternative scaling methods to log

I have data (as below). When I plot, the details of 0-10 are lost. So I scale it using a log function and then it seems that detail is lost throughout. Is there another scaling method that would work ...
0
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0answers
44 views

Normalizing logarithmic data in a range from 0 to 1

i am replicating a multilevel-analysis for my bachelor thesis (with newer data + corrections). The author i am citing used the unstandardized coefficients of every independent variable as beta ...
1
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1answer
28 views

data transformation in regression

I am going through a research paper on HbA1C (hemoglobin) management of diabetic patients. The author has used multilevel model as it has repeated measures. The DV has been log transformed. To ...
1
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0answers
22 views

Transforming Log Values in Predicted Values (Low Predicted Scores)

I have a problem with the logging of a price variable. The logging of the variable helps the model performance considerably. The value is positively skewed so this makes sense mathematically. I run ...
0
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2answers
45 views

How do I correctly compare bacterial counts from mice with different genotypes?

As far as I know, CFU counts from bacterial suspensions should approximately follow a Poisson distribution. So in order to perform a One-way Anova, a mathematical transformation to achieve normality ...
1
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1answer
58 views
3
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0answers
29 views

Nonparametric estimation of the logarithm of a density

I was wondering whether there is an equivalent to Kernel Density Estimation to estimate nonparametrically the logarithm of a density. Or if there is any nonparametric method for that. (Taking the ...
0
votes
0answers
190 views

Do we need to log-transform a variable that already is in percentage form?

I came across this website while searching for knowledge and help in statistics. As far as I know, we log-transform variable in order to avoid the heteroskedasticity problem. However, if any of the IV ...
0
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0answers
80 views

Minimizing RMSE while using a log-transformation

I am trying to fit a linear model to some data, but the dependent variable y is clearly not normally distributed. It has a heavy tail on the right. A log-transformation helps to make the ...
1
vote
1answer
36 views

Store logarithm of a variable in data set

I have seen many data sets where some of the variables are listed both with their original value and the logarithm of the variable. For instance, a data set could have the variables ...
0
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0answers
135 views

How to perform logarithmic binning

I'm trying to program (in C++ if relevant) some functionality to plot a histogram that does logarithmic binning. The range of values run from 0 to M (there is a possibility for negatives but we're not ...
0
votes
0answers
10 views

Re-arranging log-linear equation to get slope on standard (not logarithmic) scale [duplicate]

The equation for log-linear regression is: logY = mx+c [eq 1] therefore: (logY-c)/x = m [eq 2] And to get slope on standard scale we can do: exp((logY-c)/x) = exp(m) [eq 3] but Im ...
0
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0answers
59 views

Coefficient in differences-in-differences regression significant for log-level specification but not for level level

I am estimating a differences in differences model: $Y_{it} = \alpha_i + \beta_t + \tau T_iP_t + \epsilon_{it}$ where $\alpha_i$ and $\beta_t$ are fixed effects, $T_i$ is a dummy variable indicating ...
0
votes
0answers
39 views

Correction for logarithmic bias

I fitted the variable that has been log transformed (log(y + 1)) by means of mixed model. I used lme function from ...
1
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1answer
39 views

multiplying an outcome and predictor values by ten flips the sign of an effect size when log transformed. WHY?

I have a model, y~ x1 + x2 + x1*x2, where y and x1 are strongly correlated and ...
1
vote
0answers
19 views

How to use ln-transformation with loads of zeroes?

I came across a method of ln-transforming exogenous variables in non-negative data sets with loads of zeroes in a lecture. With the method proposed, one simply ln-transforms the variable in question ...
6
votes
1answer
106 views

Is there something clever I can do with a log of a sum?

In something I'm working on, the expression $$\lim_{n\rightarrow\infty}\exp\left(-\frac{1}{n}\log\left(\prod_{i=1}^{n}X_{i}+\prod_{i=1}^{n}Y_{i}\right)\right)$$ came up, in which all $X_{i}$ $iid$ and ...
3
votes
2answers
92 views

How do I change logarithmic scaled data to linear scaled data?

I am using decibels for my research, and I was told by someone that I cannot perform any statistical analyses on these measurements other than basic descriptive statistics because the data are ...
2
votes
1answer
242 views

How can I recognize when I must apply “log transformation”?

I have some time series - http://ww2.coastal.edu/kingw/statistics/R-tutorials/simplenonlinear.html In this article author try to use log transformation for pressure data. How can I recognize that ...
3
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0answers
51 views

How to interpret log-transformed predictors in probit regression?

I am running a probit model with several continous and one log-transformed predictor (firm size as total assets). I am unsure how to interpret the coefficient of -0.341 on that variable. I used the ...
1
vote
1answer
557 views

Back transformation of log10 transformed data in SPSS

I have transformed my quantitative variable by using the log10 function in order to run some parametric tests (ANOVA) but when I want to make pairwise comparisons ...
2
votes
1answer
70 views

What is the difference between a $\log_{10}$ and logit transformation?

What is the difference between a $\log_{10}$ and logit transformation? I have tried to find the answer elsewhere but cannot find a strict distinction.