Suggestion noted; thanks.
In short, the wavelet view gives a “frequency versus time” map of the loudspeaker response. The wavelet view of an ideal impulse is shown by default when the program is started. Once a measurement is loaded on the import tab, the waveleft view shows the frequency versus time map of the measurement. If the loudspeaker has, for example, “ringing” at various frequencies, the wavelet view will show patches to the right of the ideal wavelet shape at those frequencies. IIR crossovers, all-pass filters and other high-Q filtering will all cause some time smear in the loudspeaker response to the right of the “ideal” shape. Whether this is audible or not is somewhat subjective and varies with frequency; since the human auditory system performs somewhat differently at different frequencies.
With FIR filtering it’s possible to create mixed phase filters that undo some of the phase changes that cause the time smear. For example, try using auto-mag and auto-phase on a loudspeaker measurement and watch how the wavelet view changes. Or, without any measurements loaded, set channel 1 to a low-pass LR 4th order crossover filter and channel 2 to a high-pass LR 4th order crossover filter, so that the combined magnitude sums flat. What remains is a phase change due to the crossover filter. Note what the phase change looks like on the wavelet view.
For more detailed info, maybe google “wavelet analysis of loudspeakers.” Don Keele has one AES paper on the topic. A related analysis tool is the “waterfall plot” and you may find useful information on this also.