Pentti Paatero

TL;DR: BS-DISP and BS are found useful in understanding the uncertainty of factor profiles; they also suggest if the data are over-fitted by specifying too many factors, and recommendations for reporting PMF results.

TL;DR: In this article, the authors present three methods for estimating uncertainty in factor analytic models: classical bootstrap (BS), displacement of factor elements (DISP), and bootstrap enhanced by displacement of element (BS-DISP).

TL;DR: In this article, the authors evaluated the performance and the uncertainty of receptor models (RMs) in intercomparison exercises employing real-world and synthetic input datasets and concluded that RMs are capable of estimating the contribution of the major pollution source categories over a given time window with a level of accuracy that is in line with the needs of air quality management.

TL;DR: In this article, the US Environmental Protection Agency's (EPA) positive matrix factorization (PMF) data analysis tool was used to apportion organic matter (OM) as measured by HR-AMS, and rotational tools in EPA PMF were used to better characterize the solution space and pull resolved factors toward known source profiles.

TL;DR: To explore the periodicity of stem fluctuations in relation to the gravitational influence of the Moon, Fourier analysis was applied to data on variations in stem and xylem widths of Scots pine trees collected over periods of 1 to 4 months.