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| Script Name | Description | Example | Reference |
| acf | Autocorrelation function for evenly spaced one dimensional time series. | 1 |
Scargle (1981)
Scargle (1989) Koen & Lombard (1993) |
|---|---|---|---|
| afoevfor | formating AFOEV variable star data file into a MATLAB variable. | AFOEV homepage | |
| arp | model a time series by autoregressive process of order p. |
Scargle (1981)
Koen & Lombard (1993) | |
| bin_by_eye | Plot data and define binning by eye. The user mark (with the mouse) the beginning and end points of each bin. The left and right limits of each bin defined by the user are marked by cyan and red dashed lines, respectively. | ||
| binn | Binning a set of observations by equal number of observations within each bin. The program returns a matrix containing the mean "time", mean value and value standard deviation. If the number of observations is not divided by the number of points in each bin without a reminder, then the last remaining observations will not be used. | ||
| binning | Binning a set of obseravtions by equal interval of "times". | ||
| ccf | Cross correlation function for two, one dimensional time series. Use Edelson & Krolik binning method for not-equaly spaced series. | ||
| ccf_o | Cross correlation function for evenly spaced two one dimensional series. | ||
| cosbell | cosine bell function. Generating cosine bell function in the range Start to End with its inner PercentFlat part as flat function. | ||
| curvlen | calculate the length of curve by summing the distance between successive points. | ||
| cusum | cumulative sum (CUSUM) chart for detecting non stationarity in a given series mean. | Lombard & Koen (1993) | |
| equeliz | Given two matrices [JD, Mag, ...], select all the observations in the first matrix that was made in the same instant (+/-threshold) and return the in each line observations from both matrices that was made at the same instant. | ||
| extracph | Extract observation within a given phase range. extract observations with the same phase. | ||
| fitexp | LSQ fitting of exponent model, to set of data points. | ||
| fitgauss | linear least squars gaussian fit to data. | 1 | |
| fitharmo | LSQ harmonies fitting. Fit simultaneously any number of frequncies, with any number of harmonics and linear terms. | ||
| fitharmonw | LSQ harmonies fitting, with no errors (Weights=1). | ||
| fitlegen | LSQ Legendre polynomial fitting. | ||
| fitpoly | LSQ polynomial fitting. | ||
| fitslope | LSQ polynomial slope fitting (no a_0 term). | ||
| fmaxs | Given a matrix, find local maxima (in one of the columns) and return the maxima position and height. | ||
| folding | Folding a set of observations into a period. For each observation return the phase of the observation within the period. | ||
| hjd | Convert Julian Day (UTC) to Helicentric/Barycentric Julian Day (for geocentric observer). | ||
| minclp | Search for periodicity in a time series, using the minimum-curve-length method. The program calculates the curve length for each trail frequency, and return the curve length as function of frequency. minimum curve length period searching. | ||
| pdm | phase dispersion minimization. |
Linnell-Nemec & Nemec (1985)
Stellingwerf (1978) | |
| pdm_phot | Phase dispersion minimazation of photon arrival time series. | ||
| periodia | classical periodigram calculating. normalization by the variance of the data. | Scargle (1982) | |
| periodis | calculating a power spectrum to set of observations by the method of Scargle. | Scargle (1982) | |
| periodit | calculating power spectrum as function of time. | 1 | |
| perioent | periodicity search by minimizing the entropy. | 1 |
Cincotta & Pablo (1999)
Cincotta et al. (1999) Cincotta et al. (1995) |
| phot_event_me | Searching periodicity in time-tagged events using information entropy. For each trail period, the phase-magnitude space is divided into m by m cells, and the information entropy is calculated. | ||
| poisson_event | Given a vector of time-tagged events, compare the delta-time between sucssive events with the exponential distribution. | ||
| polysubs | Subtract polynomial from a data set (no errors). | ||
| runderiv | Calculate the runing derivative of an unevenly spaced time series, with flat weighting function (e.g., the slope in each window). Take into account slope-error and \chi^2. | ||
| runmean | Calculate the runing mean of an unevenly spaced time series with different weight functions and weight scheme. | ||
| sf_interp | Interpolation with structure function error propagation. The error bar in each interpolated point is calculated by adding in quadrature the the error of the neastest point with the amplitude of the stracture function at the the lag equal to the difference between the interpolated point and the nearest point. | ||
| specwin | spectral window of a time series. |
