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Translations update from Hosted Weblate #44

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97 changes: 63 additions & 34 deletions po/R-zh_Hans.po
Original file line number Diff line number Diff line change
Expand Up @@ -2,118 +2,147 @@ msgid ""
msgstr ""
"Project-Id-Version: jaspPredictiveAnalytics 0.19.2\n"
"POT-Creation-Date: 2024-10-19 02:56\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: Automatically generated\n"
"Language-Team: none\n"
"PO-Revision-Date: 2024-12-14 03:00+0000\n"
"Last-Translator: tao guo <[email protected]>\n"
"Language-Team: Chinese (Simplified Han script) <https://hosted.weblate.org/"
"projects/jasp/jasppredictiveanalytics-r/zh_Hans/>\n"
"Language: zh_Hans\n"
"MIME-Version: 1.0\n"
"Content-Type: text/plain; charset=UTF-8\n"
"Content-Transfer-Encoding: 8bit\n"
"Plural-Forms: nplurals=1; plural=0;\n"
"X-Generator: Weblate 5.9-rc\n"

msgid "Column input is wrong"
msgstr ""
msgstr "列输入错误"

msgid "<p style=\"color:tomato;\"><b>This is a warning!</b></p>\n Error proportion limit of %#.2f is crossed for the first time at data point %i in the estimation period. At this point on average %#.2f data points are estimates to be out of control with an lower limit of %#.2f and an upper limit of %#.2f </p>"
msgstr ""
"<p style=\"color:tomato;\"><b>这是一个警告!</b></p>\n"
" 在估计期内,"
"误差比例限制 %#.2f 在数据点 %i 处首次被突破。在此点之后,平均 %#.2f "
"个数据点被估计为失控,且其下限为 %#.2f,上限为 %#.2f。</p>"

msgid "<p \">No warning. The limit of %#.2f is not crossed during the estimation period.</p>"
msgstr ""
msgstr "<p>没有警告。在估计期内,误差比例限制 %#.2f 没有被突破。</p>"

msgid "<p style=\"color:tomato;\"><b>This is a warning!</b></p>\n Error proportion limit of %#.2f is crossed for the first time in %i data points in the prediction period. At this point on average %#.2f data points will be out of control with an lower limit of %#.2f and an upper limit of %#.2f </p>"
msgstr ""
"<p style=\"color:tomato;\"><b>这是一个警告!</b></p> \n"
" 在预测期内,"
"误差比例限制 %#.2f 在 %i 个数据点时首次被突破。在此点之后,平均有 %#.2f "
"个数据点将失控,其下限为 %#.2f,上限为 %#.2f。</p>"

msgid "<p \">No warning. The limit of %#.2f is not crossed during the prediction period.</p>"
msgstr ""
msgstr "<p>没有警告。在预测期内,误差比例限制 %#.2f 没有被突破。</p>"

msgid "'Time' must be in a date-like format (e.g., yyyy-mm-dd hh:mm:ss or yyyy-mm-dd)"
msgstr ""
msgstr "“时间”必须是类似日期的格式(例如:yyyy-mm-dd hh:mm:ss 或 yyyy-mm-dd)"

msgid "When 'Covariates' or 'Factors' are provided, they also need to be supplied for the future prediction period. Please provide the 'Include in Training' variable where a value of '1' indicates that this period is used for training/verification - and a value of '0' that it is used for prediction. The values for the dependent variable are allowed to be missing for the prediction period. Alternatively, you could remove the covariates and select the specific time period you want to predict under 'Future Prediction' -> 'Periodical'. That way the data is automatically extended into the future based on your settings. \n If you just want to check how well the predictions perform historically you can choose the option 'No forecast - verification only'"
msgstr ""
"当提供“协变量”或“因子”时,它们也需要在未来预测期内提供。请提供“包括在训练中”"
"变量,其中值为“1”表示该时期用于训练/验证,值为“0”表示该时期用于预测。对于预测"
"期,因变量的值可以缺失。或者,你可以删除协变量并选择您希望预测的特定时间段,"
"在“未来预测” -> “周期性”中进行设置。这样,数据将根据你的设置自动扩展到未来。"
"\n"
"如果你只是想检查预测在历史数据中的表现,可以选择“无预测 - 仅验证”选项"

msgid "The 'Include in Training' variable you provided does not consist of an uninterrupted sequence of ones (1) followed by an uninterrupted sequence of zeros (0). \n This is necessary as the module performs forecast verification on historical data to perform out-of-sample predictions for the future. Since time series data is temporally dependent, you cannot randomly allocate the ones and zeros in the 'Include in Training' variable. \n Please provide an alternative 'Include in Training' variable or only perform forecast verification/periodical prediction."
msgstr ""
"你提供的“包括在训练中”变量不是由一段连续的“1”序列后接一段连续的“0”序列组成的"
"。\n"
" 这是必要的,因为该模块在历史数据上执行预测验证,以进行未来的样本外预测。由于"
"时间序列数据是时间相关的,你不能随意分配“包括在训练中”变量中的“1”和“0”。 \n"
" 请提供一个替代的“包括在训练中”变量,或者仅执行预测验证/周期性预测。"

msgid "Basic control plot"
msgstr ""
msgstr "基本控制图表"

msgid "Autocorrelation Function Plots"
msgstr ""
msgstr "自相关函数图"

msgid "Histogram Plot"
msgstr ""
msgstr "直方图"

msgid "Mean"
msgstr ""
msgstr "平均值"

msgid "SD"
msgstr ""
msgstr "标准差"

msgid "Minimum"
msgstr ""
msgstr "最小值"

msgid "Maximum"
msgstr ""
msgstr "最大值"

msgid "Valid"
msgstr ""
msgstr "有效值"

msgid "Percent"
msgstr ""
msgstr "百分比"

msgid "Average Deviation"
msgstr ""
msgstr "平均偏差"

msgid "Too little data available for training! The 'Include in Training' variable determines which observations are used for training/verification (by setting them to one. However the selected data is not enough for the indicated Training and Prediction Window. Please select a 'Include in Training' variable that includes more observations for training or reduce the Training and Prediction Window variables."
msgstr ""
"训练数据不足!“包括在训练中”变量决定了哪些观测值用于训练/验证(通过将其设置为"
"1)。然而,所选数据不足以满足指定的训练和预测窗口。请选择一个包含更多训练数据"
"的“包括在训练中”变量,或者缩小训练和预测窗口的范围。"

msgid "The length of the training window is shorter than the number of lags selected in the 'Feature Engineering' section. This makes it impossible to compute all the values of the lagged dependent variable as there is too little data for training. Either increase the training window size or reduce the number of lags."
msgstr ""
msgstr "训练窗口的长度短于在“特征工程”部分选择的滞后期数。这使得无法计算所有滞后因变"
"量的值,因为训练数据太少。请增加训练窗口的大小或减少滞后期数。"

msgid "Running models"
msgstr ""
msgstr "运行模型"

msgid "Attempted to fit prediction model %s, but this model requires that the variance of the dependent variable is larger than zero. Either increase the training window or choose a different prediction model."
msgstr ""
msgstr "尝试拟合预测模型 %s,但该模型要求因变量的方差大于零。请增加训练窗口的大小或选"
"择一个不同的预测模型。"

msgid "CRPS"
msgstr ""
msgstr "连续排名概率得分"

msgid "DSS"
msgstr ""
msgstr "决策支持系统"

msgid "Log score"
msgstr ""
msgstr "对数分数"

msgid "Coverage"
msgstr ""
msgstr "覆盖率"

msgid "Bias"
msgstr ""
msgstr "偏差"

msgid "PIT"
msgstr ""
msgstr "概率积分变换"

msgid "MAE"
msgstr ""
msgstr "平均绝对误差"

msgid "RMSE"
msgstr ""
msgstr "均方根误差"

msgid "R%s"
msgstr ""
msgstr "R%s"

msgid "Cannot train models for future prediction. The data used for training contains only missing values or has a variance of zero, making prediction impossible. Either provide better data or change the training window for future prediction."
msgstr ""
msgstr "无法为未来预测训练模型。用于训练的数据仅包含缺失值或方差为零,导致无法进行预"
"测。请提供更好的数据,或者更改用于未来预测的训练窗口。"

msgid "Training models for future prediction"
msgstr ""
msgstr "为未来预测训练模型"

msgid "You extended the time series via periodical prediction. Please make sure that the time series is indeed periodic and matches the number of periods and units of the provided training data."
msgstr ""
msgstr "你通过周期性预测扩展了时间序列。请确保时间序列确实是周期性的,并且与提供的训"
"练数据的周期数和单位相匹配。"

msgid "Warning! The process is predicted to cross the out-of-control probability threshold for the first time at time point: %1s"
msgstr ""
msgstr "警告!预测过程中预计第一次超过失控概率阈值的时间点为:%1s"

msgid "No warning. The process is not predicted to cross the out-of-control probability threshold. The highest out-of-bound probability is %.2f%%"
msgstr ""
msgstr "没有警告。预测过程中未预计超过失控概率阈值。最高的超出范围概率为 %.2f%%"
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