Randomized Halton sequences

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Alternative sampling methods for estimating multivariate normal probabilities (2003, methodology): “Wang and Hickernell (2000) show that the elements of a randomized Halton sequence with a uniform random starting point are uniform.”
Monte Carlo and Quasi-Monte Carlo Sampling (2009, methodology): “This can also be used for randomizing Halton sequences, but in this case each coordinate is defined with a different base bj [19, 464] (see App.”
Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences (2003, methodology): “Second, the method used here to randomize a QMC sequence is based on Tuffin (1996), but other methods have also been proposed (see Owen, 1997; Wang and Hickernell, 2000).”
On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice (2006, methodology): “Another procedure, suggested by Wang and Hickernell (2000), is to eliminate the first G elements of the sequence, where G is chosen randomly.”
Good permutations for deterministic scrambled Halton sequences in terms of L2-discrepancy (2006, methodology): “Wang and Hickernell’s technique is denoted by ‘Randomized’, Morokoff and Caflish’s technique by ‘Shuffled’ and Cranley and Patterson’s technique by ‘HaltonCP ’.”