Small fixes [docs only]

joss/paper2.md

@@ -86,7 +86,7 @@ Stingray was previously described in [@stingrayjoss,@stingrayapj]. Its core func
 
 A core development goal has been to accelerate core stingray functionality, lower memory footprint, and refactor code to be extensive and interoperable, in order to prepare the library for the increasing size and complexity of modern astronomical datasets. Stingray’s core classes for Fourier analysis have shown dramatic increases in performance over time, as evident from [our benchmarks](stingray-benchmarks.stingray.science). Stingray can now produce standard timing products (e.g. a Bartlett periodogram with a Nyquist frequency of 1000 Hz and a segment size of 128 s) of a typical high-flux NICER observation in ~one second. This is the result of algorithmic improvement, and of leveraging of Just-In-Time compilation through Numba in many key components of the code. A second improvement includes large-scale reorganization of the code to avoid duplication without major breaking changes to the API, and the creation of metaclasses that enable seamless integration with other popular array formats for time series (e.g. [Pandas](https://pandas.pydata.org/), [Xarray](https://docs.xarray.dev/en/stable/index.html), [Lightkurve](docs.lightkurve.org), [Astropy Timeseries](https://docs.astropy.org/en/stable/timeseries/index.html)) and data formats ([FITS](), [HDF5](https://www.hdfgroup.org/solutions/hdf5/), [extended CSV](https://docs.astropy.org/en/stable/io/ascii/ecsv.html)).
 
-The originally planned implementation of spectral timing techniques—measures that combine Fourier analysis with spectral modelling— is now complete. Newly implemented techniques include the lag spectrum, covariance, rms, and coherence spectra. These methods are now showcased in extensive tutorials exploring NICER and NuSTAR observations.
+The originally planned implementation of spectral timing techniques — measures that combine Fourier analysis with spectral modelling - is now complete. Newly implemented techniques include the lag spectrum, covariance, rms, and coherence spectra. These methods are now showcased in extensive tutorials exploring NICER and NuSTAR observations.
 
 We introduced a wide range of new techniques particularly designed to analyse unevenly sampled data sets, responding to the growing need for these techniques with the advent of large-scale astronomical time domain surveys, subject to irregular observing constraints. Methods include Gaussian Process modeling of quasi-periodic oscillations [hubner] and Lomb-Scargle cross spectra [scargle]. We have introduced the Fourier-Domain Acceleration Search [ransom] for pulsars; the H-test [dejager] and Phase Dispersion Minimization  [stellingwerf] statistics were also introduced into the pulsar sub package to evaluate the folded profiles of pulsars. We expanded the statistical capabilities of Stingray by introducing a number of statistical evaluation functions to estimate the statistics of periodograms, with particular attention to the upper limits on variable power.