# Questions tagged [data-transformation]

Mathematical re-expression, often nonlinear, of data values. Data are often transformed either to meet the assumptions of a statistical model or to make the results of an analysis more interpretable.

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### Transformation of a fixed effect?

I'm working with a data set where I relate the response variable weight gain/loss (it goes from -110 g to 150 g) to multiple explanatory variables. It looks like this: lmer (weight.difference ~ A * B ...
22 views

### Converting data from exponential model to a linear model

This question came up recently and I am really struggling to understand how to even do this. I have just started learning statistics and would like is someone could show me how this could be done in R....
47 views

### Conversion of probabilities to rate [closed]

I need to convert this matrix of weekly probabilities to annual probabilities. However, when converting it into annual rates and transforming them into probabilities does not give reasonable values ​​(...
57 views

### Standardize first four moments: match sample moments with population moments

Let $X$ be a sample from $N(0,1)$ and $m$, $v$, $s$, $k$ denote sample mean, variance, skewness and kurtosis of $X$. I want to transform the sample $X$ such that the sample moments equal the true ...
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### Applying standard normal CDF to normal random vector

Let $\mathbf{X} = (X_1, ..., X_k)^T \sim \mathcal{N}(0, \mathbf{\Sigma})$. Transform it as follows: $$\mathbf{Y} = (\Phi(X_1), ..., \Phi(X_k)),$$ where $\Phi$ is the standard normal CDF. I need to ...
81 views

### Yeo-Johnson does not increase normality

I have used Box-Cox Yeo-Johnson transformation to make my skewed data columns less skewed and more normal so that I can remove outliers. e.g. originally most of my columns have a 'skewness' of 400! ...
31 views

### How to apply a statistical test on either a bi-modal distribution OR how to transform it to parametric?

I have lifetimevalue (LTV) data for 3 groups in my set. For each group, their respective LTV looks bi-modal. I need to test if there is a statistical significance between those groups with respect to ...
12 views

### Regression using trig-computed terms for non-time series data sets

Follwing up from my recent post: How to construct this "prediction heatmap" assuming OLS (worked out example) , I want to build my intuition around model specification for the classic ...
53 views

### Box-Cox power transformation, adding or subtracting constants, and interval scales

I am trying to understand how the Box-Cox power transformation works. So I took one of my datasets and ran the powerTransform function of the "car" package (via R Commander) after having computed a ...
29 views

### How does polynomial trend get 'detrended' by the d-differencing?

Suppose $X_t$ is an ARIMA(p, d, q) process, then so is $X_t + m(t)$ where $$m(t) =a_0 + a_1t +...+ a_{d-1}t^{d-1}$$ is some polynomial of degree $d-1$. How does such a polynomial trend get '...
372 views

### Why prices are usually not stationary, but returns are more likely to be stationary?

I read in a course material for time-series that Daily stock prices $X_t$ are in general not stationary but the daily returns defined by $Y_t := \frac{X_t - X_{t-1}}{X_{t-1}}$ may be stationary. ...
168 views

### Non linear data, need a transformation method to make the data linear

I have FX data for USD/SEK and I am trying to use the OLS to build a predictive model to predict the closing price. The closing price is the response variable. The USD/SEK opening price, low price, ...
28 views

### In what order should I perform Fisher's r-to-z transformation and correction for range restriction and measurement error on correlation coefficients?

I have a two part question; both parts relate to correcting/transforming raw correlation coefficients for the purpose of a meta-analysis. Confirming my understanding of ...
12 views

### Representing a time-series smoothed curve as a sinsoidal?

So attaches is an example of the kind of time series data I am working with. So far I have used Gaussian filters with sigma=3 and 6 to smooth the data, which has worked very well (especially sigma=3). ...
12 views

### Removing group effects from data

I have a set of data which consists of measurements from sensors for a machine. I know that depending on what the machine is doing at the time, that several different ranges of measurement data will ...
189 views