Three objective techniques used to obtain gauge-based daily precipitation analyses over global land areas are assessed. The objective techniques include the inverse-distance weighting algorithms of Cressman (1959) and Shepard (1968), and the optimal interpolation (OI) method of Gandin (1965). Intercomparisons and cross-validation tests are conducted to examine their performance over various parts of the globe where station network densities are different. The gauge data used in the examinations are quality controlled daily precipitation reports from roughly 16,000 stations over the global land areas that have been collected by the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC). Data sources include daily summary files from the Global Telecommunication System (GTS), and the CPC unified daily gauge data sets over the contiguous United States (CONUS), Mexico, and South America. All three objective techniques are capable of generating useful daily precipitation analyses with biases of generally less than 1% over most parts of the global land areas. The OI method consistently performs the best among the three techniques for almost all situations (regions, seasons, and network densities). The Shepard scheme compares reasonably well with the OI, while the Cressman method tends to generate smooth precipitation fields with wider raining areas relative to the station observations. The quality of the gauge-based analyses degrades as the network of station observations becomes sparser, although the OI technique exhibits relatively stable performance statistics over regions covered by fewer gauges.