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Exact(19)
A total of 2,235,060 SNPs with <20% missing rates were used with above mentioned phenotyping data for genomic prediction analysis.
Missing rates were calculated for each field.
In general, the missing rates were low.
Missing rates were negligible or zero for all variables.
Genotypes missing rates were low (range: 1 - 6%).
Percentage rates of error and missing rates were calculated.
Similar(41)
The average missing rates are 0.30, 0.20, and 0.10, respectively.
Various datasets with different missing rates are generated randomly for simulating the reality situation for modeling the real situation of missing matrix, randomly.
The missing rating is denoted by (r_{i,j}=0).
Although this architecture reduces the area overhead dramatically, we find that the fault missing rate is still high if single-sample checking (SSC) is used.
Since the properties of fault missing rate are similar for m = 2 n ± 1, the simulations for m = 2 n + 1 are not given here.
More suggestions(15)
absence rates were
short rates were
missing bags were
missing data were
missing people were
missing postcodes were
missing cleavages were
missing rates ranged
missing clusters were
missing responses were
missing remains were
missing observations were
missing genotypes were
missing answers were
missing assessments were
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