This thesis concerns the analysis and sensitivity of nonlinear eigenvalue problems for matrices and linear operators. The first part illustrates that lack of normality may result in catastrophic ill-conditioned eigenvalue problem. Linearization of rational eigenvalue problems for both operators over finite and infinite dimensional spaces are considered. The standard approach is to multiply by the least common denominator in the rational term and apply a well known linearization technique to the polynomial eigenvalue problem. However, the symmetry of the original problem is lost, which may result in a more ill-conditioned problem. In this thesis, an alternative linearization method is used and the sensitivity of the two different linearizations are studied. Moreover, this work contains numerically solved rational eigenvalue problems with applications in photonic crystals. For these examples the pseudospectra is used to show how well-conditioned the problems are which indicates whether the solutions are reliable or not.