| Abstract : | Discrepancy in the values Hubble parameter estimated from the high and low redshift observations is one of the biggest challenges in modern cosmology. To probe this issue, it is important to estimate the cosmological parameters in an accurate and model-independent way. It is also important to develop data analysis techniques that are more efficient without losing out on the required accuracy. In this work, we use principal component analysis to reduce the dimensionality of the parameter space. We start with a higher dimensional parameter space and compute the principal components that can describe the cosmological evolution using fewer degrees of freedom. Using simulated data we test the validity of this approach. Then we use real observational data on the late Universe expansion history to constrain the cosmological parameters and compare it with the other estimates in the literature. |
