  This note is devoted to discussing multivariate approximation of continuous
functions on $[0,1]^d$ with analytic Korobov kernels in the worst and average
case settings. We only consider algorithms that use finitely many evaluations
of arbitrary continuous linear functionals. We study EC-$(s, t)$-weak
tractability under the absolute or normalized error criterion, and obtain
necessary and sufficient conditions for $0<\min(s,t)<1$ and $\max(s,t)\le 1$ in
the worst case setting and for $s,t>0$ in the average case setting.
