The Heart Rate Variability (HRV) oscillations are commonly driven by multiple sources, but the most known external driver is the respiration, via the Respiratory Sinus Arrhythmia (RSA), i.e. an increased HR during inhalation and a decreased HR during exhalation. The quantification of this interaction can be investigated with different methods. Two of them are the subspace projections and the Time Frequency (TF) representations. Additionally, The HRV is commonly described with the tachogram, but other tools, such as the Integral Pulse Frequency Modulation (IPFM) model and the point process model, have also been used. Each of these methods produces a different HRV representation. The objective of this study is to compare the quantification of the RSA using the different HRV representations, while changes in the autonomic regulation of the heart are induced. For this, a dataset containing electrocardiogram and inductance plethysmograph signals from 14 volunteers was used during a protocol in which the sympathetic and parasympathetic branches of the ANS were selectively blocked combining pharmacological blockades and posture changes. After R-peak detection, the HRV representations were derived via the interpolated tachogram, the IPFM model and the point process model. For each of these time series, the power in the High Frequency (HF) band was computed and the RSA was quantified via subspace projections and a quadratic TF representation. Finally, the RSA estimates difference for the three HRV representations was assessed via Kruskall Wallis tests and differences on the RSA due to posture changes were evaluated with Friedman tests. The RSA estimates did not differ significantly with the three HRV representations (p>0.05). The strength of the RSA was significantly lower in standing compared to supine position (p<0.05) without pharmacological blockade. The results suggest that the selection of a HRV representation is irrelevant for the analysis of the RSA in this database.