SLOPES computes six least-squares linear regression lines for bivariate datasets of the form (x_i,y_i) with unknown population distributions. Measurement errors, censoring (nondetections) or other complications are not treated. The lines are: the ordinary least-squares regression of y on x, OLS(Y|X); the inverse regression of x on y, OLS(X_Y); the angular bisector of the OLS lines; the orthogonal regression line; the reduced major axis, and the mean-OLS line. The latter four regressions treat the variables symmetrically, while the first two regressions are asymmetrical. Uncertainties for the regression coefficients of each method are estimated via asymptotic formulae, bootstrap resampling, and bivariate normal simulation. These methods, derivation of the regression coefficient uncertainties, and discussions of their use are provided in three papers listed below. The user is encouraged to read and reference these studies.

XPHOT is an IDL implementation of a non-parametric method for estimating the apparent and intrinsic broad-band fluxes and absorbing X-ray column densities of weak X-ray sources. XPHOT is intended for faint sources with greater than ∼5-7 counts but fewer than 100-300 counts where parametric spectral fitting methods will be superior. This method is similar to the long-standing use of color-magnitude diagrams in optical and infrared astronomy, with X-ray median energy replacing color index and X-ray source counts replacing magnitude. Though XPHOT was calibrated for thermal spectra characteristic of stars in young stellar clusters, recalibration should be possible for some other classes of faint X-ray sources such as extragalactic active galactic nuclei.

TCF calculates a periodogram designed to detect exoplanet transits after the light curve has been differenced. It is a matched filter for a periodic double-spike pattern. The difference operator that can be used independently for detrending a light curve; it is also embedded in ARIMA (autoregressive integrated moving average) Box-Jenkins modeling.

The Periodogram Comparison for Optimizing Small Transiting Planet Detection R code compares two periodogram algorithms for detecting transiting exoplanets: the Box-fitting Least Squares (BLS) and the Transit Comb Filter (TCF). It calculates the False Alarm Probability (FAP) based on extreme value theory and signal-to-noise ratio (SNR) metrics to quantify periodogram peak significance. The comparison approach is aimed at optimizing the detection of small transiting planets in future transiting exoplanet surveys. The code can be extended for comparing any set of periodograms.